Blockchain
Do you want to find out what Blockchain is, how it works, and what it can do for you?This book could be the answer you are looking for...This book is the ultimate beginner's guide to understanding blockchain technology, cryptocurrencies, bitcoin and the future of money.In this guide, we shall be discussing everything there is to know about cryptocurrencies, their impact on the future of money and trade, and most importantly, how you can prepare yourself for the disruptive technology that is the blockchain.Here is just some of the information covered in this book: The History of Money What is the Blockchain Technology? History of the Blockchain A Chronological Development of Blockchain Related Technologies Benefits of the Blockchain Technology Disadvantages of Using Blockchain Technology Understanding Ethereum How Ethereum Developed How Ethereum Works How Smart Contracts Work The Application Possibilities for Smart Contracts How Mining Works How to Get Started with Blockchain and Implementing Blockchain into Business Operations Blockchain-Based Applications You Can Integrate Into Your Business How to Get Started with Smart Contract and Ethereum Web Development Understanding Cryptocurrencies and their Emergence How Cryptocurrencies Work Bitcoin Lifecycle: How Cryptocurrency Transactions Work How to Invest In Blockchain and Cryptocurrencies And Much More! Scroll to the top of the page and select the Add to Cart button to learn more about Blockchain!
Software Ecosystems, Sustainability and Human Values in the Social Web
This book constitutes extended revised selected papers presented during the 8th Workshop of Human-Computer Interaction Aspects to the Social Web, WAIHCWS 2017, held in Joinville, Brazil, in October 2017, and during the 9th Workshop of Human-Computer Interaction Aspects to the Social Web, WAIHCWS 2018, held in Bel矇m, Brazil, in October 2018. The 5 full papers presented were thoroughly reviewed and selected from 14 submissions for WAIHCWS 2017 and 3 full papers were selected for publication from 20 submissions for WAIHCWS 2018. The authors were given the opportunity to extend and revise the papers after the conference. The topics included in this volume cover the following fields connected to the social web: user experience, emotion analysis, interoperability, systems-of-information systems, knowledge-intensive processes, ontology, transportation domain, mobile systems, privacy policies, digital legacy, social networks, recommendation models, scientific events, accessible web, software ecosystems, and sustainability.
Learning SQL
As data floods into your company, you need to put it to work right away--and SQL is the best tool for the job. With the latest edition of this introductory guide, author Alan Beaulieu helps developers get up to speed with SQL fundamentals for writing database applications, performing administrative tasks, and generating reports. You'll find new chapters on SQL and big data, analytic functions, and working with very large databases. Each chapter presents a self-contained lesson on a key SQL concept or technique using numerous illustrations and annotated examples. Exercises let you practice the skills you learn. Knowledge of SQL is a must for interacting with data. With Learning SQL, you'll quickly discover how to put the power and flexibility of this language to work. Move quickly through SQL basics and several advanced features Use SQL data statements to generate, manipulate, and retrieve data Create database objects, such as tables, indexes, and constraints with SQL schema statements Learn how datasets interact with queries; understand the importance of subqueries Convert and manipulate data with SQL's built-in functions and use conditional logic in data statements
How To Recover Deleted Files
If you want to discover how to solve your problems regarding loss data in your computer then, check this"How To Recover Deleted Files" guide. In this step-by-step guide, you will reap the following benefits: - Resolve data loss problems. - Learn how to prevent data loss. - Learn how to recover data due to system boot issue. - Learn how to recover data due to hard disk issue. - Discover how to recover Office data files. - Impress your friends to recover their computer from viruses, corrupted registry and files. - Discover how to make use of the computer data recovery tools. - Recover operating system from an unstable program. - Learn how to back-up your files and folders. - And much more.HowExpert publushes quick 'how to' guides on all topics from A to Z by everyday experts.
Human Activity Recognition using Wearable SensorsAn Introduction into how Deep Learning ca
Technological advancements in healthcare can contribute unquestionably in reducing healthcare strains by ensuring clinicians, doctors and other medical staff operate and conduct their daily activities more efficiently in the hospital vicinity. Since the turn of the 21st century, Human Activity Recognition (HAR) has undergone significant research in the healthcare domain. HAR utilised with powerful technologies can benefit remote patient monitoring, the elderly, patients suffering from chronic illness and ambient assisted living. Human activity recognition has shown to be effective in benefiting clinicians in the treatment and remote monitoring of patients. This field is not only vital for diagnosis and treatment, but also an assessment of how likely a medical patient will fall ill or die from certain diseases or health problems. To show the great importance of activity recognition in the health sector, analytically driving an improvement in accuracy in classifying patients' activities improves the relationship of patients and clinicians as well as reducing the possibility of a fatality. With Artificial Intelligence at the forefront of its revolutionary capabilities, a bright future is in store if we can implement it beneficially into our healthcare service. This book reveals how.
Integer Programming and Combinatorial Optimization
This book constitutes the refereed proceedings of the 21st International Conference on Integer Programming and Combinatorial Optimization, IPCO 2020, held in London, UK, in June 2020. The 33 full versions of extended abstracts presented were carefully reviewed and selected from 126 submissions. The conference is a forum for researchers and practitioners working on various aspects of integer programming and combinatorial optimization. The aim is to present recent developments in theory, computation, and applications in these areas.
Computer ArchitectureDigital Circuits to Microprocessors
An introductory text to computer architecture, this comprehensive volume covers the concepts from logic gates to advanced computer architecture. It comes with a full spectrum of exercises and web-downloadable support materials, including assembler and simulator, which can be used in the context of different courses. The authors also make available a hardware description, which can be used in labs and assignments, for hands-on experimentation with an actual, simple processor.This unique compendium is a useful reference for undergraduates, graduates and professionals majoring in computer engineering, circuits and systems, software engineering, biomedical engineering and aerospace engineering.Related Link(s)
Data, Engineering and Applications
This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.
Big DataConcepts, Warehousing, and Analytics
Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes. The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems. This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.
Simulation Science
This book constitutes the refereed proceedings of the Second International Workshop on Simulation Science, held in Clausthal-Zellerfeld, in May 2019. The 12 full papers were carefully reviewed and selected from 47 submissions. The papers are organized according to the following topics: optimization and distributed simulations; simulation of materials; self-organized and porous structures; simulation of materials: finite element and multiscale methods.
WebSci ’19Proceedings of the11th ACM Conference on Web Science
It is our great pleasure to welcome you to the 11th ACM Conference on Web Science (Websci'19), June 30 - July 3, 2019, Boston, MA, USA.This year, the conference theme is "Synergies for the Good: The Web and Society". We welcomedinterdisciplinary contributions, especially those that had a broad perspective on the web, includingthose that combined analyses of web data with other types of data (e.g., from surveys or interviews)to better understand user behavior (online and offline); carried out longitudinal studies; presentedsuccessful cases of interdisciplinary and cross-disciplinary web research; used mixed-methodapproaches; critically reflected on the methods used; discussed responsible forms of Web Science(e.g. regarding standards, methods, generalizability of results); and/or those that reflected on thesocietal impact of web research, how the web is perceived in the media and in society, and whetherthis clashes with our self-image of Web Science. Thus, research on the interaction of society and theweb was invited, and we received submissions highlighting web implications, synergies derived, and how the web as a socio-technical system will evolve in future.WebSci'19 was a unique conference where a multitude of disciplines converged in a creative andcritical dialogue with the aim of understanding the web and its impacts. WebSci'19 welcomedparticipation from diverse fields including (but not limited to) art, anthropology, computer andinformation sciences, communication, economics, humanities, informatics, law, linguistics, philosophy, political science, psychology, and sociology. Following the tradition of earlierconferences, contributions to WebSci'19 aimed to cross traditional disciplinary boundaries. Thecommunity engaged with novel and thought-provoking ideas and discussed original research, work in progress, analysis, and practice in the field of Web Science, its current theoretical, methodological, and epistemological challenges as well as Web practices of individuals, collectives, institutions, and platforms. This year we were very pleased to accept 41 submissions for the regular research track chosen outof 130 submissions. We are grateful for the support of the Program Committee which consisted of16 senior members and 66 regular members who selected an interesting, varied, exciting programcomprising 31 long and 10 short papers. In addition to the posters selected from the Call forPosters, eight contributions were invited to be presented as a poster because they sparked fruitfuldiscussions among the reviewers and were deemed to be of great interest and relevance to theWebSci'19 community.This year WebSci'19 encouraged authors to particularly prepare and publish reproducibilityinformation of conducted research and resources, such as source code and datasets. Authors wereasked to add (if possible) a link (e.g. DOI or URL) to data or any other information relevant to theirsubmission. With this measure WebSci'19 aimed at raising awareness of the reproducibility issueand demonstrated that, as a community-driven conference, it subscribes to and actively promotesOpen Science principles in research.
Storytelling With Data
Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become--or teach others to be--a powerful data storyteller. Let's practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller storytelling with data's foundational lessons, Let's practice! delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes: ● Practice with Cole: exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation ● Practice on your own: thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions ● Practice at work: practical guidance and hands-on exercises for applying storytelling with data lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact The lessons and exercises found within this comprehensive guide will empower you to master--or develop in others--data storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories!
Data Preprocessing with Python for Absolute Beginners
Are you looking for a hands-on approach to learn Data Preprocessing techniques fast?Do you need to start learning Python for Data Preparation from Scratch?This book is for you.This book is dedicated to data preparation and explains how to perform different data preparation techniques on a variety of datasets using various data preparation libraries written in the Python programming language. It is suggested that you use this book for data preparation purposes only and not for data science or machine learning.For the application of data preparation in data science and machine learning, read this book in conjunction with dedicated books on machine learning and data science.This book explains the process of data preparation using various libraries from scratch. All the codes and datasets have been provided. However, to download data preparation libraries, you will need the internet. In addition to beginners to data preparation with Python, this book can also be used as a reference manual by intermediate and experienced programmers as it contains data preparation code samples using multiple data visualization libraries.What this book offers... The book follows a very simple approach. It is divided into nine chapters. Chapter 1 introduces the basic concept of data preparation, along with the installation steps for the software that we will need to perform data preparation in this book. Chapter 1 also contains a crash course on Python. A brief overview of different data types is given in Chapter 2. Chapter 3 explains how to handle missing values in the data, while the categorical encoding of numeric data is explained in Chapter 4. Data discretization is presented in Chapter 5. Chapter 6 explains the process of handline outliers, while Chapter 7 explains how to scale features in the dataset. Handling of mixed and datetime data type is explained in Chapter 8, while data balancing and resampling has been explained in Chapter 9. A full data preparation final project is also available at the end of the book. In each chapter, different types of data preparation techniques have been explained theoretically, followed by practical examples. Each chapter also contains an exercise that students can use to evaluate their understanding of the concepts explained in the chapter.Clear and Easy to Understand SolutionsAll solutions in this book are extensively tested by a group of beta readers. The solutions provided are simplified as much as possible so that they can serve as examples for you to refer to when you are learning a new skill.Topics Covered: What Is Data PreparationPython Crash CourseDifferent Libraries for Data PreparationUnderstanding Data TypesHandling Missing DataEncoding Categorical DataData DiscretizationOutlier HandlingFeature ScalingHandling Mixed and DateTime VariablesHandling Imbalanced DatasetsA Complete Data Preparation PipelineProject 1 - Data PreparationProject 2 - Classification ProjectProject 3 - Regression ProjectClick the BUY button and download the book now to start learning Data Preprocessing Using Python.
Data Science Building Blocks
Data Science Building Blocks is a result of the authors' many years of industry experience in data science and their various interactions with learners whose conversations also figure in this content. The book is aimed at familiarising aspirants and beginners with the basics of data science. These building blocks will help you build your analytics dream house. When it is done, don't forget to invite us and share your success story over a cup of coffee.
MySQL 8 Query Performance TuningA Systematic Method for Improving Execution Speeds
Identify, analyze, and improve poorly performing queries that damage user experience and lead to lost revenue for your business. This book will help you make query tuning an integral part of your daily routine through a multi-step process that includes monitoring of execution times, identifying candidate queries for optimization, analyzing their current performance, and improving them to deliver results faster and with less overhead. Author Jesper Krogh systematically discusses each of these steps along with the data sources and the tools used to perform them. MySQL 8 Query Performance Tuning aims to help you improve query performance using a wide range of strategies. You will know how to analyze queries using both the traditional EXPLAIN command as well as the new EXPLAIN ANALYZE tool. You also will see how to use the Visual Explain feature to provide a visually-oriented view of an execution plan. Coverage of indexes includes indexing strategies and index statistics, and you will learn how histograms can be used to provide input on skewed data distributions that the optimizer can use to improve query performance. You will learn about locks, and how to investigate locking issues. And you will come away with an understanding of how the MySQL optimizer works, including the new hash join algorithm, and how to change the optimizer's behavior when needed to deliver faster execution times. You will gain the tools and skills needed to delight application users and to squeeze the most value from corporate computing resources. What You Will LearnMonitor query performance to identify poor performersChoose queries to optimize that will provide the greatest gainAnalyze queries using tools such as EXPLAIN ANALYZE and Visual ExplainImprove slow queries through a wide range of strategiesProperly deploy indexes and histograms to aid in creating fast execution plansUnderstand and analyze locks to resolve contention and increase throughputWho This Book Is ForDatabase administrators and SQL developers who are familiar with MySQL and need to participate in query tuning. While some experience with MySQL is required, no prior knowledge of query performance tuning is needed.
Data Structures and Program Design Using Java
Data structures provide a means to managing large amounts of information such as large databases, using SEO effectively, and creating Internet/Web indexing services. This book is designed to present fundamentals of data structures for beginners using the Java programming language in a friendly, self-teaching format. Practical analogies using real world applications are integrated throughout the text to explain technical concepts. The book includes a variety of end-of-chapter practice exercises, e.g., programming, theoretical, and multiple-choice. Features: Covers data structure fundamentals using JavaNumerous tips, analogies, and practical applications enhance understanding of subjects under discussion"Frequently Asked Questions" integrated throughout the text clarify and explain conceptsIncludes a variety of end-of-chapter exercises, e.g., programming, theoretical, and multiple choice
The Data Catalog
Apply this definitive guide to data catalogs and select the feature set needed to empower your data citizens in their quest for faster time to insight. The data catalog may be the most important breakthrough in data management in the last decade, ranking alongside the advent of the data warehouse. The latter enabled business consumers to conduct their own analyses to obtain insights themselves. The data catalog is the next wave of this, empowering business users even further to drastically reduce time to insight, despite the rising tide of data flooding the enterprise.Use this book as a guide to provide a broad overview of the most popular Machine Learning (ML) data catalog products, and perform due diligence using the extensive features list. Consider graphical user interface (GUI) design issues such as layout and navigation, as well as scalability in terms of how the catalog will handle your current and anticipated data and metadata needs.This book is organized into three sections: Chapters 1 and 2 reveal the rationale for a data catalog and share how data scientists, data administrators, and curators fare with and without a data catalog. Chapters 3-10 present the many different types of data catalogs. Chapters 11 and 12 provide an extensive features' list, current trends, and visions for the future.
Architecting for ScaleHow to Maintain High Availability and Manage Risk in the Cloud
Every day, companies struggle to scale critical applications. As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. With the popularity of software as a service, scaling has never been more important. Updated with an expanded focus on modern architecture paradigms such as microservices and cloud computing, this practical guide provides techniques for building systems that can handle huge quantities of traffic, data, and demand--without affecting the quality your customers expect. Architects, managers, and directors in engineering and operations organizations will learn how to build applications at scale that run more smoothly and reliably to meet the needs of customers. Learn how scaling affects the availability of your services, why that matters, and how to improve it Dive into a modern service-based application architecture that ensures high availability and reduces the effects of service failures Explore the Single Team Owned Service Architecture paradigm (STOSA)--a model for scaling your development organization in tandem with your application Understand, measure, and mitigate risk in your systems Use the cloud to build highly scalable applications
Pods ’19
It is our great pleasure to welcome you to the 38th ACM SIGMOD-SIGACT-SIGAI Symposiumon Principles of Database Systems (PODS 2019), held in Amsterdam, The Netherlands, on July 1-3, 2019, in conjunction with the 2019 ACM SIGMOD International Conference on Managementof Data.Since the first edition of the symposium in 1982, the PODS papers are distinguished by arigorous approach to widely diverse problems in data management, often bringing to beartechniques from a variety of different areas, including computational logic, finite model theory, computational complexity, algorithm design and analysis, programming languages, and artificialintelligence.The PODS Symposia study data management challenges in a variety of application contexts, including more recently parallel computation, streaming and realtime data, and graph dataprocessing algorithms. PODS has a tradition of being the premier international conference onthe theoretical and foundational aspects of data management, and the interested reader isreferred to the web page https: //databasetheory.org/pods for information on the history of thisconference series.This year's symposium continues this tradition and invited for submission papers providingoriginal, substantial contributions in one or more of the following categories: a) deep theoretical exploration of topical areas central to data management;b) new formal frameworks that aim at providing a basis for deeper theoretical investigation ofimportant emerging issues in data management; andc) validation of theoretical approaches from the lens of practical applicability in datamanagement. Papers in this track should provide an experimental evaluation that gives newinsight in established theories. Besides, they should provide a clear message to the databasetheory community as to which aspects need further (theoretical) investigation, based on theexperimental findings. As in previous years, PODS operated with two submission cycles. The first cycle allowed for thepossibility for papers to be revised and resubmitted. For the first cycle, 36 papers weresubmitted, 4 of which were directly selected for inclusion in the proceedings, and 8 were invitedfor a resubmission after a revision. The quality of the revised papers increased substantially withrespect to the first submission, and all of the revised papers were selected for the proceedings.For the second cycle, 51 papers were submitted, 17 of which were selected, resulting in 29 papersselected overall from a total number of 87 submissions.This volume contains the proceedings of PODS 2019, which include papers on the keynoteaddressed by Cynthia Dwork of Harvard University, the two invited tutorials, one of the twoGems talks, and 29 contributions that were selected by the Program Committee for presentationat the symposium.
Practical Oracle SQL
Write powerful queries using as much of the feature-rich Oracle SQL language as possible, progressing beyond the simple queries of basic SQL as standardized in SQL-92.Both standard SQL and Oracle's own extensions to the language have progressed far over the decades in terms of how much you can work with your data in a single, albeit sometimes complex, SQL statement. If you already know the basics of SQL, this book provides many examples of how to write even more advanced SQL to huge benefit in your applications, such as: Pivoting rows to columns and columns to rowsRecursion in SQL with MODEL and WITH clausesAnswering Top-N questionsForecasting with linear regressionsRow pattern matching to group or distribute rowsUsing MATCH_RECOGNIZE as a row processing engineThe process of starting from simpler statements in SQL, and gradually working those statements stepwise into more complexstatements that deliver powerful results, is covered in each example. By trying out the recipes and examples for yourself, you will put together the building blocks into powerful SQL statements that will make your application run circles around your competitors. What You Will LearnTake full advantage of advanced and modern features in Oracle SQLRecognize when modern SQL constructs can help create better applicationsImprove SQL query building skills through stepwise refinementApply set-based thinking to process more data in fewer queriesMake cross-row calculations with analytic functionsSearch for patterns across multiple rows using row pattern matchingBreak complex calculations into smaller steps with subquery factoringWho This Book Is ForOracle Database developers who already knowsome SQL, but rarely use features of the language beyond the SQL-92 standard. And it is for developers who would like to apply the more modern features of Oracle SQL, but don't know where to start. The book also is for those who want to write increasingly complex queries in a stepwise and understandable manner. Experienced developers will use the book to develop more efficient queries using the advanced features of the Oracle SQL language.
Fundamentals of Software Architecture
Salary surveys worldwide regularly place software architect in the top 10 best jobs, yet no real guide exists to help developers become architects. Until now. This book provides the first comprehensive overview of software architecture's many aspects. Aspiring and existing architects alike will examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics. Mark Richards and Neal Ford--hands-on practitioners who have taught software architecture classes professionally for years--focus on architecture principles that apply across all technology stacks. You'll explore software architecture in a modern light, taking into account all the innovations of the past decade. This book examines: Architecture patterns: The technical basis for many architectural decisions Components: Identification, coupling, cohesion, partitioning, and granularity Soft skills: Effective team management, meetings, negotiation, presentations, and more Modernity: Engineering practices and operational approaches that have changed radically in the past few years Architecture as an engineering discipline: Repeatable results, metrics, and concrete valuations that add rigor to software architecture
Practical Oracle Cloud InfrastructureInfrastructure as a Service, Autonomous Database, Man
Use this fast-paced and comprehensive guide to build cloud-based solutions on Oracle Cloud Infrastructure. You will understand cloud infrastructure, and learn how to launch new applications and move existing applications to Oracle Cloud. Emerging trends in software architecture are covered such as autonomous platforms, infrastructure as code, containerized applications, cloud-based container orchestration with managed Kubernetes, and running serverless workloads using open-source tools. Practical examples are provided.This book teaches you how to self-provision the cloud resources you require to run and scale your custom cloud-based applications using a convenient web console and programmable APIs, and you will learn how to manage your infrastructure as code with Terraform. You will be able to plan, design, implement, deploy, run, and monitor your production-grade and fault-tolerant cloud software solutions in Oracle's data centers across the world, paying only for the resources you actually use. Oracle Cloud Infrastructure is part of Oracle's new generation cloud that delivers a complete and well-integrated set of Infrastructure as a Service (IaaS) capabilities (compute, storage, networking), edge services (DNS, web application firewall), and Platform as a Service (PaaS) capabilities (such as Oracle Autonomous Database which supports both transactional and analytical workloads, the certified and fully managed Oracle Kubernetes Engine, and a serverless platform based on an open-source Fn Project).What You Will LearnBuild software solutions on Oracle CloudAutomate cloud infrastructure with CLI and TerraformFollow best practices for architecting on Oracle CloudEmploy Oracle Autonomous Database to obtain valuable data insightsRun containerized applications on Oracle's Container Engine for KubernetesUnderstand the emerging Cloud Native ecosystemWho This Book Is For Cloud architects, developers, DevOps engineers, and technology students and others who want to learn how to build cloud-based systems on Oracle Cloud Infrastructure (OCI) leveraging a broad range of OCI Infrastructure as a Service (IAAS) capabilities, Oracle Autonomous Database, and Oracle's Container Engine for Kubernetes. Readers should have a working knowledge of Linux, exposure to programming, and a basic understanding of networking concepts. All exercises in the book can be done at no cost with a 30-day Oracle Cloud trial.
Data Analytics
Say goodbye to scratching your head in confusionThis data analytics book could be the answer you're looking for...This book has lots of valuable eye-opening information about data analytics, which will help you understand the concept of data mining, data collection, big data analytics for business and business intelligence concepts.With this book, not only will you understand all the internal nitty-gritties about data analytics, you will also understand why data analytics is changing the business arena. You'll realize that the high-performance analytics will enable you to do stuff that you never thought about before probably because the volumes of data were just too big (among other reasons) and so much more.We'll begin by first examining what data analytics really means and what it entails. Do not fret when you meet challenging terms as you read on, as this book includes detailed explanations of words you may not understand.Here are just some of the topics that are discussed within this book: Overview Of Data Analytics: What Is Data Analytics (And Big Data Analytics)? Data Analytics And Business Intelligence Data Analysis And Data Analytics Data Mining Data Collection Types Of Data Analytics The Process: The Lifecycle Of Big Data Analytics Behavioral Analytics: Using Big Data Analytics To Find Hidden Customer Behavior Patterns Further Pattern Discovery In Advanced Analytics: Machine Learning And Much, Much More Get the book now and learn more about data analytics!
Data ScienceA Comprehensive Guide to Data Science, Data Analytics, Data Mining, Artificial
If you want to learn about data science and big data, then keep reading... Two manuscripts in one book: Data Science: What You Need to Know About Data Analytics, Data Mining, Regression Analysis, Artificial Intelligence, Big Data for Business, Data Visualization, Database Querying, and Machine Learning Big Data: A Guide to Big Data Trends, Artificial Intelligence, Machine Learning, Predictive Analytics, Internet of Things, Data Science, Data Analytics, Business Intelligence, and Data Mining This book will discuss everything that you need to know when it comes to working in the field of data science. This world has changed, and with the modern technology that we have, it is easier than ever for companies to amass a large amount of data on the industry, on their competition, on their products, and their customers. Gathering the data is the easy part, though. Being able to sort through this data and understand what it is saying is going to be a unique challenge all on its own. This is where the process and field of data science can come in. There is so much that we can explore and learn about when it comes to the world of data science, and this ultimate guide is here to help you navigate through these specialties. You will see just how important the ideas of data mining, data analytics, and even artificial intelligence are to our world as a whole today. Some of the topics covered in part 1 of this book include: What is Data Science? What Exactly Does a Data Scientist Do? A Look at What Data Analytics Is All About What is Data Mining and How Does It Fit in with Data Science? Regression Analysis Why is Data Visualization So Important When It Comes to Understanding Your Data? How to work with Database Querying A Look at Artificial Intelligence What is Machine Learning and How Is It Different from Artificial Intelligence? What is the Future of Artificial Intelligence and Machine Learning? And much more! Some of the topics covered in part 2 of this book include: What is big data, and why is it important? The five V's behind big data How big data is already impacting your life, and where big data may be headed How big data and your everyday devices and appliances will come together in unexpected ways via the Internet of Things How companies and governments are using predictive analytics to get ahead of the competition or improve service How big data is used for fraud detection How big data can train intelligent computer systems The many ways large corporations are benefiting from big data and the tools that use it like machine learning, AI, and predictive analytics Upcoming trends in big data that are sure to have a large impact on your future Artificial intelligence, and how big data drives its development What machine learning is and how it is tied to big data The relationship between big data, data analytics, and business intelligence Insights into how big data impacts privacy issues The pros and cons regarding big data And much, much more! So if you want to learn more about data science and big data, click the "add to cart" button!
Data Science Programming All-in-one for Dummies
Your logical, linear guide to the fundamentals of data science programming Data science is exploding--in a good way--with a forecast of 1.7 megabytes of new information created every second for each human being on the planet by 2020 and 11.5 million job openings by 2026. It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you're a beginning student or already mid-career, get your copy now and add even more meaning to your life--and everyone else's!
Data Science
Did you know that the value of data usage has increased job opportunities, but that there are few specialists?These days, everyone is aware of the role that data can play, whether it is an election, business or education. But how can you start working in a wide interdisciplinary field that is occupied with so much hype?This book, Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't, presents you with a step-by-step approach to Data Science as well as secrets only known by the best Data Scientists. It combines analytical engineering, Machine Learning, Big Data, Data Mining, and Statistics in an easy to read and digest method.Data gathered from scientific measurements, customers, IoT sensors, and so on is very important only when one can draw meaning from it. Data Scientists are professionals that help disclose interesting and rewarding challenges of exploring, observing, analyzing, and interpreting data. To do that, they apply special techniques that help them discover the meaning of data. Becoming the best Data Scientist is more than just mastering analytic tools and techniques. The real deal lies in the way you apply your creative ability like expert Data Scientists. This book will help you discover that and get you there.The goal with Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't is to help you expand your skills from being a basic Data Scientist to becoming an expert Data Scientist ready to solve real-world data centric issues. At the end of this book, you will learn how to combine Machine Learning, Data Mining, analytics, and programming, and extract real knowledge from data. As you read, you will discover important statistical techniques and algorithms that are helpful in learning Data Science. When you have finished, you will have a strong foundation to help you explore many other fields related to Data Science.This book will discuss the following topics: What Data Science is What it takes to become an expert in Data Science Best Data Mining techniques to apply in data Data visualization Logistic regression Data engineering Machine Learning Big Data Analytics And much more! Don't waste any time. Grab your copy today and learn quick tips from the best Data scientists!
Data Science
Do you want to expand your skills from being a basic Data Scientist to becoming an expert Data Scientist ready to solve real-world data centric issues?Exploring this book could be a step in the right direction...2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, and Machine Learning for Beginners Part one of this book will cover topics such as: What Data Science is What it takes to become an expert in Data Science Best Data Mining techniques to apply in data Data visualization Logistic regression Data engineering Machine Learning Big Data Analytics And much more! Part 2 of this book will discuss the following topics: How Big Data works and why it is so important How to do an explorative data analysis Working with data mining How to mine text to get the data Some amazing machine learning algorithms to help with data science How to do data modeling Data visualization How to use data science to help your business grow Tips to help you get started with data science And much, much more! So if you want to learn more about data science, click "buy now"!
Data Analytics
If you want to learn about data analytics and data mining then keep reading...2 comprehensive manuscripts in 1 book Data Analytics: An Essential Beginner's Guide To Data Mining, Data Collection, Big Data Analytics For Business, And Business Intelligence Concepts Data Mining: The Data Mining Guide for Beginners, Including Applications for Business, Data Mining Techniques, Concepts, and More With this book, not only will you understand all the internal nitty-gritties about data analytics and data mining, you will also understand why data analytics and data mining is changing the business arena. You'll realize that the high-performance analytics will enable you to do stuff that you never thought about before probably because the volumes of data were just too big (among other reasons) and so much more. Here are just some of the topics that are discussed in the first part of this book: Overview Of Data Analytics: What Is Data Analytics (And Big Data Analytics)? Data Analytics And Business Intelligence Data Analysis And Data Analytics Data Mining Data Collection Types Of Data Analytics The Process: The Lifecycle Of Big Data Analytics Behavioral Analytics: Using Big Data Analytics To Find Hidden Customer Behavior Patterns Further Pattern Discovery In Advanced Analytics: Machine Learning And Much, Much More In part 2 of this book, you will learn the following: Model creation How to prepare your data How to clean your data Data Mining Similarity and distances of data The effect of data distribution Association pattern mining What is cluster analysis? What is an outlier in data mining? How to deal with outliers in data mining Methods of identifying outliers in data Applications of data mining in the business industry So if you are serious about becoming an expert in data analytics and data mining, start with this book by clicking "buy now"!
Microsoft SQL Server 2019: A Beginner’s Guide, Seventh Edition
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Get Up to Speed on Microsoft(R) SQL Server(R) 2019 Quickly and EasilyStart working with Microsoft SQL Server 2019 in no time with help from this thoroughly revised, practical resource. Filled with real-world examples and hands-on exercises, Microsoft SQL Server 2019: A Beginner's Guide, Seventh Edition starts by explaining fundamental relational database system concepts. From there, you'll learn how to write Transact-SQL statements, execute simple and complex database queries, handle system administration and security, and use powerful analysis and reporting tools. New topics such as SQL and JSON support, graph databases, and support for machine learning with R and Python are also covered in this step-by-step tutorial.- Install, configure, and customize Microsoft SQL Server 2019- Create and modify database objects with Transact-SQL statements- Write stored procedures and user-defined functions- Handle backup and recovery, and automate administrative tasks- Tune your database system for optimal availability and reliability- Secure your system using authentication, encryption, and authorization- Work with SQL Server Analysis Services, Reporting Services, and other BI tools- Gain knowledge of relational storage, presentation, and retrieval of data stored in the JSON format- Manage graphs using SQL Server Graph Databases- Learn about machine learning support for R and Python
Ciencia de los datos
2 manuscritos completos en 1 libro Ciencia de los datos: Lo que saben los mejores cient穩ficos de datos sobre el an獺lisis de datos, miner穩a de datos, estad穩sticas, aprendizaje autom獺tico y Big Data - que usted desconoce Ciencia de Datos para Empresas: Modelo Predictivo, Miner穩a de Datos, An獺lisis de Datos, An獺lisis de Regresi籀n, Consulta de Bases de Datos y Aprendizaje Autom獺tico para Principiantes Los datos recopilados de mediciones cient穩ficas, clientes, sensores de IoT (Internet de las cosas), etc., son muy importantes solo cuando uno puede extraer un significado de ellos. Los cient穩ficos de datos son profesionales que ayudan a revelar desaf穩os interesantes y gratificantes de explorar, observar, analizar y a interpretar datos. Para hacerlo, aplican t矇cnicas especiales que les ayudan a descubrir el significado de los datos. Convertirse en el mejor cient穩fico de datos es algo m獺s que dominar las herramientas y t矇cnicas anal穩ticas. El verdadero problema radica en la forma de aplicar la capacidad creativa como expertos cient穩ficos de datos. Este libro le ayudar獺 a descubrirlo y llevarlo hasta all穩. El objetivo de "Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't" (Ciencia de datos: lo que saben los mejores cient穩ficos de datos sobre el an獺lisis de datos, miner穩a de datos, estad穩sticas, aprendizaje autom獺tico y Big Data - que usted desconoce) es ayudarle a expandir sus habilidades de ser un cient穩fico de datos b獺sico a convertirse en un cient穩fico de datos experto listo para resolver problemas centrados en datos del mundo real. Al final de este libro, aprender獺 c籀mo combinar Aprendizaje autom獺tico, Miner穩a de datos, an獺lisis y programaci籀n, y extraer conocimiento real de los datos. A medida que lo lea, descubrir獺 importantes t矇cnicas estad穩sticas y algoritmos que son 繳tiles para aprender la Ciencia de los Datos. Cuando haya terminado, tendr獺 una base s籀lida que lo ayudar獺 a explorar muchos otros campos relacionados con la ciencia de datos. La primera parte de este libro incluye: Lo que la ciencia de datos es Lo que se necesita para convertirse en un experto en Ciencias de Datos Las mejores t矇cnicas de miner穩a de datos para aplicar en datos Visualizaci籀n de datos Regresi籀n log穩stica Ingenier穩a de datos Aprendizaje autom獺tico Anal穩tica de Big Data 癒Y mucho m獺s! Al leer la segunda parte de este libro, usted: 聶Qu矇 es la Ciencia de Datos? C籀mo funcionan los Grandes vol繳menes de datos y por qu矇 es tan importante C籀mo hacer un an獺lisis exploratorio de datos Trabajar con miner穩a de datos C籀mo extraer texto para obtener los datos. Algunos algoritmos asombrosos de aprendizaje autom獺tico para ayudar con la Ciencia de Datos C籀mo hacer modelado de datos Visualizaci籀n de datos C籀mo utilizar la Ciencia de Datos para ayudar a que su negocio crezca Consejos para ayudarle a comenzar con la Ciencia de Datos 癒Y mucho, mucho m獺s! Obtenga este libro ahora para conocer m獺s sobre la Ciencia de los datos y Ciencia de Datos para empresas!
Ciencia de los datos
聶Sab穩a usted que el valor del uso de datos ha aumentado las oportunidades de empleo, pero que actualmente hay pocos especialistas?En estos d穩as, todos son conscientes del papel que pueden desempe簽ar los datos, ya sea en una elecci籀n, en un negocio o en la educaci籀n. Pero, 聶c籀mo puede empezar a trabajar en este amplio campo interdisciplinario ocupado con tanta propaganda?Este libro, "Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't" (Ciencia de datos: lo que saben los mejores cient穩ficos de datos sobre el an獺lisis de datos, miner穩a de datos, estad穩sticas, aprendizaje autom獺tico y big data - que usted desconoce), le presenta un enfoque paso a paso de la ciencia de datos, as穩 como los secretos solo conocidos por los mejores cient穩ficos de datos. Combina la ingenier穩a anal穩tica, aprendizaje autom獺tico, Big Data, miner穩a de datos y estad穩sticas en un m矇todo f獺cil de leer y digerir.Los datos recopilados de mediciones cient穩ficas, clientes, sensores de IoT (Internet de las cosas), etc., son muy importantes solo cuando uno puede extraer un significado de ellos. Los cient穩ficos de datos son profesionales que ayudan a revelar desaf穩os interesantes y gratificantes de explorar, observar, analizar y a interpretar datos. Para hacerlo, aplican t矇cnicas especiales que les ayudan a descubrir el significado de los datos. Convertirse en el mejor cient穩fico de datos es algo m獺s que dominar las herramientas y t矇cnicas anal穩ticas. El verdadero problema radica en la forma de aplicar la capacidad creativa como expertos cient穩ficos de datos. Este libro le ayudar獺 a descubrirlo y llevarlo hasta all穩.El objetivo de "Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't" (Ciencia de datos: lo que saben los mejores cient穩ficos de datos sobre el an獺lisis de datos, miner穩a de datos, estad穩sticas, aprendizaje autom獺tico y Big Data - que usted desconoce) es ayudarle a expandir sus habilidades de ser un cient穩fico de datos b獺sico a convertirse en un cient穩fico de datos experto listo para resolver problemas centrados en datos del mundo real. Al final de este libro, aprender獺 c籀mo combinar Aprendizaje autom獺tico, Miner穩a de datos, an獺lisis y programaci籀n, y extraer conocimiento real de los datos. A medida que lo lea, descubrir獺 importantes t矇cnicas estad穩sticas y algoritmos que son 繳tiles para aprender la Ciencia de los Datos. Cuando haya terminado, tendr獺 una base s籀lida que lo ayudar獺 a explorar muchos otros campos relacionados con la ciencia de datos.Este libro tratar獺 sobre los siguientes temas: Lo que la ciencia de datos es Lo que se necesita para convertirse en un experto en Ciencias de Datos Las mejores t矇cnicas de miner穩a de datos para aplicar en datos Visualizaci籀n de datos Regresi籀n log穩stica Ingenier穩a de datos Aprendizaje autom獺tico Anal穩tica de Big Data 癒Y mucho m獺s! 癒Obtenga este libro ahora para aprender m獺s sobre la ciencia de datos!
Jumpstart Snowflake
Explore the modern market of data analytics platforms and the benefits of using Snowflake computing, the data warehouse built for the cloud. With the rise of cloud technologies, organizations prefer to deploy their analytics using cloud providers such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Cloud vendors are offering modern data platforms for building cloud analytics solutions to collect data and consolidate into single storage solutions that provide insights for business users. The core of any analytics framework is the data warehouse, and previously customers did not have many choices of platform to use. Snowflake was built specifically for the cloud and it is a true game changer for the analytics market. This book will help onboard you to Snowflake, present best practices to deploy, and use the Snowflake data warehouse. In addition, it covers modern analytics architecture and use cases. It provides use cases of integration with leading analytics software such as Matillion ETL, Tableau, and Databricks. Finally, it covers migration scenarios for on-premise legacy data warehouses. What You Will Learn Know the key functionalities of SnowflakeSet up security and access with clusterBulk load data into Snowflake using the COPY commandMigrate from a legacy data warehouse to Snowflakeintegrate the Snowflake data platform with modern business intelligence (BI) and data integration tools Who This Book Is For Those working with data warehouse and business intelligence (BI) technologies, and existing and potential Snowflake users
Salesforce Platform App Builder Certification
New or intermediate developers will want to use this hands-on guide to prepare for the Salesforce Certified Platform App Builder credential, awarded for designing, building, and implementing applications using the declarative customization capabilities of the Salesforce Platform. This is the first book available covering this content, and Salesforce training is very costly. This book is filled with real-world examples and hands-on exercises, enabling you to prepare for the certification exam in a short span of time. Multiple-choice study questions and exercises are included to help you apply what you learn in each chapter.Author Rakesh Gupta explains Salesforce Platform fundamentals, including knowledge about the limitations of the declarative platform and when to use programmatic development versus the AppExchange. Data management and data analytics are covered. And you will learn how to set up organization-wide features that affect the look and feel of your application. Sandbox design patterns and process automation tools available in Salesforce are discussed and you will know when to use them. You will become familiar with a wide array of topics, including designing a mobile app and reporting in Salesforce. What You Will Learn Know when to use declarative development versus programmatic development versus the AppExchangeUnderstand the Salesforce data model, field type (when to use which fields), and how and when to use an external object in SalesforceBe familiar with security and settings in SalesforceSee how easily users can migrate to the Lightning experience from the classic platformImplement business process automation using declarative featuresApply the automation process in SalesforceUtilize Process Builder and manage its power to automate business processesUse sandboxes and deployment tools Who This Book Is For New or intermediate Salesforce developers or anyone in the Salesforce development arena who wants to learn or explore the platform
Database Design and Relational Theory
Create database designs that scale, meet business requirements, and inherently work toward keeping your data structured and usable in the face of changing business models and software systems.This book is about database design theory. Design theory is the scientific foundation for database design, just as the relational model is the scientific foundation for database technology in general. Databases lie at the heart of so much of what we do in the computing world that negative impacts of poor design can be extraordinarily widespread. This second edition includes greatly expanded coverage of exotic and little understood normal forms such as: essential tuple normal form (ETNF), redundancy free normal form (RFNF), superkey normal form (SKNF), sixth normal form (6NF), and domain key normal form (DKNF). Also included are new appendixes, including one that provides an in-depth look into the crucial notion of data consistency.Sequencing of topics has been improved, and many explanations and examples have been rewritten and clarified based upon the author's teaching of the content in instructor-led courses. This book aims to be different from other books on design by bridging the gap between the theory of design and the practice of design. The book explains theory in a way that practitioners should be able to understand, and it explains why that theory is of considerable practical importance. Reading this book provides you with an important theoretical grounding on which to do the practical work of database design. Reading the book also helps you in going to and understanding the more academic texts as you build your base of knowledge and expertise. Anyone with a professional interest in database design can benefit from using this book as a stepping-stone toward a more rigorous design approach and more lasting database models.What You Will LearnUnderstand what design theory is and is notBe aware of the two different goals of normalizationKnow which normal forms are truly significant Apply design theory in practice Be familiar with techniques for dealing with redundancy Understand what consistency is and why it is crucially important Who This Book Is ForThose having a professional interest in database design, including data and database administrators; educators and students specializing in database matters; information modelers and database designers; DBMS designers, implementers, and other database vendor personnel; and database consultants. The book is product independent.
The Definitive Guide to Aws Application Integration
Build reliable, asynchronous, and distributed applications using message queuing and task orchestration capabilities of Amazon Web Services (AWS) Application Integration. This book prepares you to build distributed applications and administrators, and manage queues, workflows, and state machines.You'll start by reviewing key AWS prerequisite services such as EC2, Lambda, S3, DynamoDB, CloudWatch, and IAM. Simple Queue Service (SQS) and SNS Simple Notification Service (SNS) are then covered to show how applications interact with each other in a reliable and resilient fashion. Next, workflow building with (Simple Workflow Service (SWF) for orchestration of tasks is explained and in the final chapter learn the techniques for building a state using Step Functions, Simple Workflow Service along with Flow Framework. The book illustrates all the concepts using numerous examples that work with SDK, CLI, and Console. Most of the codeexamples are in Java, followed by Python and JavaScript. What You Will LearnUnderstand the important prerequisites of AWS, such as EC2, Lambda, S3, and DynamoDBWork with SQS, SNS, and SWS functionsReview Step functionsWho This Book Is ForAWS developers and software developers proficient in Java, Python and JavaScript.
The Definitive Guide to Aws Infrastructure Automation
Discover the pillars of AWS infrastructure automation, starting with API-driven infrastructure concepts and its immediate benefits such as increased agility, automation of the infrastructure life cycle, and flexibility in experimenting with new architectures. With this base established, the book discusses infrastructure-as-code concepts in a general form, establishing principled outcomes such as security and reproducibility. Inescapably, we delve into how these concepts enable and underpin the DevOps movement. The Definitive Guide to AWS Infrastructure Automation begins by discussing services and tools that enable infrastructure-as-code solutions; first stop: AWS's CloudFormation service. You'll then cover the ever-expanding ecosystem of tooling emerging in this space, including CloudFormation wrappers such as Troposphere and orchestrators such as Sceptre, to completely independent third-party tools such as Terraform and Pulumi. As a bonus, you'll also work with AWS' newly-released CDK (Cloud Development Kit). You'll then look at how to implement modular, robust, and extensible solutions across a few examples -- in the process building out each solution with several different tools to compare and contrast the strengths and weaknesses of each. By the end of the journey, you will have gained a wide knowledge of both the AWS-provided and third-party ecosystem of infrastructure-as-code/provisioning tools, and the strengths and weaknesses of each. You'll possess a mental framework for how to craft an infrastructure-as-code solution to solve future problems based on examples discussed throughout the book. You'll also have a demonstrable understanding of the hands-on operation of each tool, situational appropriateness of each tool, and how to leverage the tool day to day. What You Will Learn Discover the technological and organizational benefits to infrastructure-as-code solutions Examine the overall landscape of infrastructure-as-code tooling and solutions available to consumers of AWS services See the strengths and weaknesses of these tools relative to one another as examined through hands-on implementation of several solutions Gain hands-on experience, best practices, and tips and tricks learned through several years' real-world experience delivering solutions using these very tools in a wide variety of scenarios Engineer solid solutions that leave room for new requirements and changes without requiring needless refactoring Who This Book Is For DevOps engineers, cloud engineers and architects focused on the AWS ecosystem, software engineers/developers working within the AWS ecosystem, and engineering leaders looking for best practices.
Mastering Salesforce Devops
This practical guide brings DevOps principles to Salesforce development. It fits together two major movements within the IT world: the movement to Software/Platform as a Service (SaaS/PaaS), and the DevOps movement. While SaaS and PaaS allow companies to invest in their core competencies rather than maintain their own infrastructure, the goal of DevOps is to optimize the process of delivering software innovation and value. The release of Salesforce DX in late 2017 unlocks the possibility of a true DevOps workflow on Salesforce. But DevOps is new to the Salesforce world and there is not a widespread understanding of its goals and methods, and so adoption of Salesforce DX is still in the early stages. Mastering Salesforce DevOps explains how to build a powerful and comprehensive DevOps workflow for Salesforce--allowing you to finally deploy the world's most innovative platform using the world's most effective and efficient techniques. It addresses theneed for a comprehensive guide to DevOps for Salesforce, allowing teams to bring proven practices from the IT world to resolve the hardest problems facing Salesforce developers today. What You Will LearnImprove company performance and software delivery performance using Salesforce DXTranslate DevOps concepts into the unique language and practices of SalesforceUnderstand why and how you can implement Salesforce DX to achieve greater productivity and innovationEnable continuous delivery on SalesforceBuild packages and architect code so it can be deployed easilyAllow admins to participate in what has traditionally been a developer workflowKnow the techniques for reducing the stress and risk of deploymentApply the full range of automated tests that can be used on Salesforce Who This Book Is for Salesforce developers, release managers, and those managing Salesforce development teams who need a guide to DevOps, and DevOps specialists who need to apply familiar concepts to Salesforce
Database Internals
When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals. Throughout the book, you'll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You'll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed. This book examines: Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each Storage building blocks: Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log Distributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns Database clusters: Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency
Deep Learning from Scratch
With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many software engineers. This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You璽 ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You璽 ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you璽 ll be set up for success on all future deep learning projects. This book provides: Extremely clear and thorough mental models璽 accompanied by working code examples and mathematical explanations璽 for understanding neural networks Methods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented framework Working implementations and clear-cut explanations of convolutional and recurrent neural networks Implementation of these neural network concepts using the popular PyTorch framework
Mastering Spark With R
If you're like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions
Discovery Science
This book constitutes the proceedings of the 22nd International Conference on Discovery Science, DS 2019, held in Split, Coratia, in October 2019. The 21 full and 19 short papers presented together with 3 abstracts of invited talks in this volume were carefully reviewed and selected from 63 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in the following topical sections: Advanced Machine Learning; Applications; Data and Knowledge Representation; Feature Importance; Interpretable Machine Learning; Networks; Pattern Discovery; and Time Series.
Chinese Computational Linguistics
This book constitutes the proceedings of the 18th China National Conference on Computational Linguistics, CCL 2019, held in Kunming, China, in October 2019. The 56 full papers presented in this volume were carefully reviewed and selected from 134 submissions. They were organized in topical sections named: linguistics and cognitive science, fundamental theory and methods of computational linguistics, information retrieval and question answering, text classification and summarization, knowledge graph and information extraction, machine translation and multilingual information processing, minority language processing, language resource and evaluation, social computing and sentiment analysis, NLP applications.
Query Store for SQL Server 2019
Apply the new Query Store feature to identify and fix poorly performing queries in SQL Server.Query Store is an important and recent feature in SQL Server that provides insight into the details of query execution and how that execution has changed over time. Query Store helps to identify queries that aren't performing well, or that have regressed in their performance. Query Store provides detailed information such as wait stats that you need to resolve root causes, and it allows you to force the use of a known good execution plan. With SQL Server 2017 and later you can automate the correction of regressions in performance. Query Store for SQL Server 2019 helps you protect your database's performance during upgrades of applications or version of SQL Server. The book provides fundamental information on how Query Store works and best practices for implementation and use. You will learn to run and interpret built-in reports, configure automatic plan correction, and troubleshoot queries using Query Store when needed. Query Store for SQL Server 2019 helps you master Query Store and bring value to your organization through consistent query execution times and automate correction of regressions. What You'll LearnApply best practices in implementing Query Store on production serversDetect and correct regressions in query performanceLower the risk of performance degradation following an upgradeUse tools and techniques to get the most from Query StoreAutomate regression correction and other uses of Query StoreWho This Book Is For SQL Server developers and administrators responsible for query performance on SQL Server. Anyone responsible for identifying poorly performing queries will be able to use Query Store to find these queries and resolve the underlying issues.
Introducing Mysql Shell
Use MySQL Shell, the first modern and advanced client for connecting to and interacting with MySQL. It supports SQL, Python, and JavaScript. That's right! You can write Python scripts and execute them within the shell interactively, or in batch mode. The level of automation available from Python combined with batch mode is especially helpful to those practicing DevOps methods in their database environments. Introducing MySQL Shell covers everything you need to know about MySQL Shell. You will learn how to use the shell for SQL, as well as the new application programming interfaces for working with a document store and even automating your management of MySQL servers using Python. The book includes a look at the supporting technologies and concepts such as JSON, schema-less documents, NoSQL, MySQL Replication, Group Replication, InnoDB Cluster, and more.MySQL Shell is the client that developers and databaseadministrators have been waiting for. Far more powerful than the legacy client, MySQL Shell enables levels of automation that are useful not only for MySQL, but in the broader context of your career as well. Automate your work and build skills in one of the most in-demand languages. With MySQL Shell, you can do both! What You'll LearnUse MySQL Shell with the newest features in MySQL 8Discover what a Document Store is and how to manage it with MySQL ShellConfigure Group Replication and InnoDB Cluster from MySQL ShellUnderstand the new MySQL Python application programming interfacesWrite Python scripts for managing your data and the MySQL high availability featuresWho This Book Is For Developers and database professionals who want to automate their work and remain on the cutting edge of what MySQLhas to offer. Anyone not happy with the limited automation capabilities of the legacy command-line client will find much to like in this book on the MySQL Shell that supports powerful automation through the Python scripting language.
Practical Salesforce Development Without Code
Use this hands-on guide to build powerful solutions on the Salesforce platform without using a single line of code. This revised and expanded second edition includes Process Builder, Flow Builder, Lightning App Builder, Lightning Bolt Solutions, and more.Practical Salesforce Development Without Code shows you how to unlock the power of the Salesforce platform to solve real business problems. Adhering to Salesforce's "clicks, not code" mantra, Salesforce expert Phil Weinmeister walks Salesforce newcomers and veterans through different business problems and identifies effective--and proven--approaches to solutions using the platform's declarative framework.By adopting this book as your guide, you will learn how to deliver business solutions within Salesforce by combining analysis, creativity, and logic with core elements such as validation rules, workflow rules, processes, flows, formula fields, and Lightning apps. In addition, Weinmeister dissects and explains themost useful functions and features for declarative developers and shows you how to use them. Best of all, Weinmeister uses real-life business scenarios and visuals. Applying the lessons learned from this how-to guide will ultimately save you time and ensure that your clients or internal customers are enabled, equipped, and empowered. What You'll Learn Build objects, fields, and relationships to establish a sensible data modelAutomate business processes by using Workflow, Process Builder, and FlowUtilize functions and develop formulas effectively for a variety of business needsDevelop approval processes to handle exception scenariosEmploy actions to easily create efficient and relevant user experiencesManage your environments and deploy your solutions Who This Book Is forBusiness analysts, Salesforceadministrators, and Salesforce developers
Intelligent Computing Methodologies
This two-volume set of LNCS 11643 and LNCS 11644 constitutes - in conjunction with the volume LNAI 11645 - the refereed proceedings of the 15th International Conference on Intelligent Computing, ICIC 2019, held in Nanchang, China, in August 2019. The 217 full papers of the three proceedings volumes were carefully reviewed and selected from 609 submissions.The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is "Advanced Intelligent Computing Methodologies and Applications." Papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology.
Data Science Strategy for Dummies
All the answers to your data science questions Over half of all businesses are using data science to generate insights and value from big data. How are they doing it? Data Science Strategy For Dummies answers all your questions about how to build a data science capability from scratch, starting with the "what" and the "why" of data science and covering what it takes to lead and nurture a top-notch team of data scientists. With this book, you'll learn how to incorporate data science as a strategic function into any business, large or small. Find solutions to your real-life challenges as you uncover the stories and value hidden within data. Learn exactly what data science is and why it's important Adopt a data-driven mindset as the foundation to success Understand the processes and common roadblocks behind data science Keep your data science program focused on generating business value Nurture a top-quality data science team In non-technical language, Data Science Strategy For Dummies outlines new perspectives and strategies to effectively lead analytics and data science functions to create real value.
