Tableau for Salesforce
Tableau is a powerful data visualization tool, and Salesforce CRM is the most successful customer relationship management software. Companies often use these two tools to analyze data and create visualizations. The book starts with an introduction to both Tableau and Salesforce CRM. It then goes on to show how you can connect Tableau with Salesforce CRM and link the two tools. Then, it walks through some of the key features of this connection that allow for seamless data analysis and visualization. It then moves on to advanced use cases, combining Salesforce and Tableau for advanced analytics and decision-making
Engineering Data Mesh in Azure Cloud
Overcome data mesh adoption challenges using the cloud-scale analytics framework and make your data analytics landscape agile and efficient by using standard architecture patterns for diverse analytical workloadsKey FeaturesDelve into core data mesh concepts and apply them to real-world situationsSafely reassess and redesign your framework for seamless data mesh integrationConquer practical challenges, from domain organization to building data contractsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDecentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help.The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you'll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud.The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI).By the end of this book, you'll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.What you will learnBuild a strategy to implement a data mesh in Azure CloudPlan your data mesh journey to build a collaborative analytics platformAddress challenges in designing, building, and managing data contractsGet to grips with monitoring and governing a data meshUnderstand how to build a self-service portal for analyticsDesign and implement a secure data mesh architectureResolve practical challenges related to data mesh adoptionWho this book is forThis book is for chief data officers and data architects of large and medium-size organizations who are struggling to maintain silos of data and analytics projects. Data architects and data engineers looking to understand data mesh and how it can help their organizations democratize data and analytics will also benefit from this book. Prior knowledge of managing centralized analytical systems, as well as experience with building data lakes, data warehouses, data pipelines, data integrations, and transformations is needed to get the most out of this book.Table of ContentsIntroducing Data MeshesBuilding a Data Mesh StrategyDeploying a Data Mesh Using the Azure Cloud-Scale Analytics FrameworkBuilding a Data Mesh Governance Framework Using Microsoft Azure ServicesSecurity Architecture for Data MeshesAutomating Deployment through Azure Resource Manager and Azure DevOpsBuilding a Self-Service Portal for Common Data Mesh OperationsHow to Design, Build, and Manage Data ContractsData Quality ManagementMaster Data ManagementMonitoring and Data ObservabilityMonitoring Data Mesh Costs and Building a Cross-Charging Model(N.B. Please use the Look Inside option to see further chapters)
Investigating Discourse and Texts
This volume delves into Corpus-Assisted Discourse Analysis (CADS), providing a deeper understanding of the social practices that underpin discourse creation and the recurring characteristics of their associated textual elements. Divided into two sections, the volume clarifies CADS methodologies and showcases their applications, shedding light on a broad spectrum of topics such as sentiment analysis, corpus annotation, recurrent constructions at the intersection of lexicon and syntax, as well as strategies shaping the discourse of politics, media and healthcare. Its clear style, methodological depth, and practical case studies make it suitable for academics and PhD students involved in CADS.
Trends and Applications in Knowledge Discovery and Data Mining
This book constitutes the workshops that have been held in conjunction with the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan, during May 25-28, 2023. For RAFDA 2024, Workshop on Research and Applications of Foundation Models for Data Mining and Affective Computing, 15 submissions have been received and 9 full papers have been accepted for publication. For IWTA 2024, International Workshop on Temporal Analytics, 4 full papers have been accepted from a total of 6 submissions.
MyData and Data Sovereignty in the Age of AI
The era of data sovereignty has arrived and the world is transforming into a data-driven society. This book begins its discussion with ownership of data from a big data and personal data perspective. Innovative services that combine technologies such as blockchain, VR/XR, and AI are being released every day, but it is personal data that eventually leads to innovative services.Accordingly, ownership, scope and method of use of data are changing. It is changing from centralized to decentralized, from corporate ownership to personal ownership, and from big data-based to personal data-based use.In terms of data sovereignty and GDPR, MyData and the expected changes it will brings are described, and the impact of AI on MyData is dealt with in depth. The author presents an approach for human-centric & practical MyData implementation, and specifically proposes a technical approach for the utilization of personal data based on data sovereignty.In addition to policy discussions on data sovereignty and issues surrounding personal data, the studies on the application of data technology are summarized at a glance. It is a book that can enhance the understanding of changes in MyData technology, policies, and markets.
Advances in Intelligent Data Analysis XXII
The two volume set LNCS 14641 and 14642 constitutes the proceedings of the 22nd International Symposium on Intelligent Data Analysis, IDA 2024, which was held in Stockholm, Sweden, during April 24-26, 2024. The 40 full and 3 short papers included in the proceedings were carefully reviewed and selected from 94 submissions. IDA is an international symposium presenting advances in the intelligent analysis of data. Distinguishing characteristics of IDA are its focus on novel, inspiring ideas, its focus on research, and its relatively small scale.
Web and Big Data
The 4-volume set LNCS 14331, 14332, 14333, and 14334 constitutes the refereed proceedings of the 7th International Joint Conference, APWeb-WAIM 2023, which took place in Wuhan, China, in October 2023. The total of 138 papers included in the proceedings were carefully reviewed and selected from 434 submissions. They focus on innovative ideas, original research findings, case study results, and experienced insights in the areas of the World Wide Web and big data, covering Web technologies, database systems, information management, software engineering, knowledge graph, recommend system and big data.
Advances in Intelligent Data Analysis XXII
The two volume set LNCS 14641 and 14642 constitutes the proceedings of the 22nd International Symposium on Intelligent Data Analysis, IDA 2024, which was held in Stockholm, Sweden, during April 24-26, 2024. The 40 full and 3 short papers included in the proceedings were carefully reviewed and selected from 94 submissions. IDA is an international symposium presenting advances in the intelligent analysis of data. Distinguishing characteristics of IDA are its focus on novel, inspiring ideas, its focus on research, and its relatively small scale.
Web and Big Data
The 4-volume set LNCS 14331, 14332, 14333, and 14334 constitutes the refereed proceedings of the 7th International Joint Conference, APWeb-WAIM 2023, which took place in Wuhan, China, in October 2023. The total of 138 papers included in the proceedings were carefully reviewed and selected from 434 submissions. They focus on innovative ideas, original research findings, case study results, and experienced insights in the areas of the World Wide Web and big data, covering Web technologies, database systems, information management, software engineering, knowledge graph, recommend system and big data.
Big Data and Analytics
Unveiling insights, unleashing potential: Navigating the depths of big data and analytics for a data-driven tomorrowKEY FEATURES ● Learn about big data and how it helps businesses innovate, grow, and make decisions efficiently.● Learn about data collection, storage, processing, and analysis, along with tools and methods.● Discover real-life examples of big data applications across industries, addressing challenges like privacy and security.DESCRIPTION Big data and analytics is an indispensable guide that navigates the complex data management and analysis. This comprehensive book covers the core principles, processes, and tools, ensuring readers grasp the essentials and progress to advanced applications.It will help you understand the different analysis types like descriptive, predictive, and prescriptive. Learn about NoSQL databases and their benefits over SQL. The book centers on Hadoop, explaining its features, versions, and main components like HDFS (storage) and MapReduce (processing). Explore MapReduce and YARN for efficient data processing. Gain insights into MongoDB and Hive, popular tools in the big data landscape.WHAT YOU WILL LEARN● Grasp big data fundamentals and applications.● Master descriptive, predictive, and prescriptive analytics.● Understand HDFS, MapReduce, YARN, and their functionalities.● Explore data storage, retrieval, and manipulation in a NoSQL database.● Gain practical insights and apply them to real-world scenarios.WHO THIS BOOK IS FORThis book caters to a diverse audience, including data professionals, analysts, IT managers, and business intelligence practitioners.
Data Cleaning with Power BI
Unlock the full potential of your data by mastering the art of cleaning, preparing, and transforming data with Power BI for smarter insights and data visualizationsKey Features: Implement best practices for connecting, preparing, cleaning, and analyzing multiple sources of data using Power BIConduct exploratory data analysis (EDA) using DAX, PowerQuery, and the M languageApply your newfound knowledge to tackle common data challenges for visualizations in Power BIPurchase of the print or Kindle book includes a free PDF eBookBook Description: Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization.This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier.By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.What You Will Learn: Connect to data sources using both import and DirectQuery optionsUse the Query Editor to apply data transformationsTransform your data using the M query languageDesign clean and optimized data models by creating relationships and DAX calculationsPerform exploratory data analysis using Power BIAddress the most common data challenges with best practicesExplore the benefits of using OpenAI, ChatGPT, and Microsoft Copilot for simplifying data cleaningWho this book is for: If you're a data analyst, business intelligence professional, business analyst, data scientist, or anyone who works with data on a regular basis, this book is for you. It's a useful resource for anyone who wants to gain a deeper understanding of data quality issues and best practices for data cleaning in Power BI. If you have a basic knowledge of BI tools and concepts, this book will help you advance your skills in Power BI.
Python for Natural Language Processing
Since the last edition of this book (2014), progress has been astonishing in all areas of Natural Language Processing, with recent achievements in Text Generation that spurred a media interest going beyond the traditional academic circles. Text Processing has meanwhile become a mainstream industrial tool that is used, to various extents, by countless companies. As such, a revision of this book was deemed necessary to catch up with the recent breakthroughs, and the author discusses models and architectures that have been instrumental in the recent progress of Natural Language Processing.As in the first two editions, the intention is to expose the reader to the theories used in Natural Language Processing, and to programming examples that are essential for a deep understanding of the concepts. Although present in the previous two editions, Machine Learning is now even more pregnant, having replaced many of the earlier techniques to process text. Many new techniques build on the availability of text. Using Python notebooks, the reader will be able to load small corpora, format text, apply the models through executing pieces of code, gradually discover the theoretical parts by possibly modifying the code or the parameters, and traverse theories and concrete problems through a constant interaction between the user and the machine. The data sizes and hardware requirements are kept to a reasonable minimum so that a user can see instantly, or at least quickly, the results of most experiments on most machines.The book does not assume a deep knowledge of Python, and an introduction to this language aimed at Text Processing is given in Ch. 2, which will enable the reader to touch all the programming concepts, including NumPy arrays and PyTorch tensors as fundamental structures to represent and process numerical data in Python, or Keras for training Neural Networks to classify texts. Covering topics like Word Segmentation and Part-of-Speech and Sequence Annotation, the textbook also gives an in-depth overview of Transformers (for instance, BERT), Self-Attention and Sequence-to-Sequence Architectures.
Data-Centric Machine Learning with Python
Join the data-centric revolution and master the concepts, techniques, and algorithms shaping the future of AI and ML development, using PythonKey Features- Grasp the principles of data centricity and apply them to real-world scenarios- Gain experience with quality data collection, labeling, and synthetic data creation using Python- Develop essential skills for building reliable, responsible, and ethical machine learning solutions- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets.This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of 'small data'. Delving into the building blocks of data-centric ML/AI, you'll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you'll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you'll get a roadmap for implementing data-centric ML/AI in diverse applications in Python.By the end of this book, you'll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability.What you will learn- Understand the impact of input data quality compared to model selection and tuning- Recognize the crucial role of subject-matter experts in effective model development- Implement data cleaning, labeling, and augmentation best practices- Explore common synthetic data generation techniques and their applications- Apply synthetic data generation techniques using common Python packages- Detect and mitigate bias in a dataset using best-practice techniques- Understand the importance of reliability, responsibility, and ethical considerations in ML/AIWho this book is forThis book is for data science professionals and machine learning enthusiasts looking to understand the concept of data-centricity, its benefits over a model-centric approach, and the practical application of a best-practice data-centric approach in their work. This book is also for other data professionals and senior leaders who want to explore the tools and techniques to improve data quality and create opportunities for small data ML/AI in their organizations.Table of Contents- Exploring Data-Centric Machine Learning- From Model-Centric to Data-Centric - ML's Evolution- Principles of Data-Centric ML- Data Labeling Is a Collaborative Process- Techniques for Data Cleaning- Techniques for Programmatic Labeling in Machine Learning- Using Synthetic Data in Data-Centric Machine Learning- Techniques for Identifying and Removing Bias- Dealing with Edge Cases and Rare Events in Machine Learning- Kick-Starting Your Journey in Data-Centric Machine Learning
Interaction of Symbols
Interaction of Symbols is a book for everyone engaged with icon design. It presents a theory of how icons work: symbols in an icon interact to evoke meaning. From this theory flow design principles and practices based on evidence from Design and other disciplines such as Psychology, Perception, and Cognition. The theory, principles, and practices impact how all symbol-based communications are conceived, designed, and applied.The book focuses on icons that elicit a concept without any previous training or use of language. Findings from twenty years' worth of empirical design research studies explore, illustrate, and support each principle, process, and recommendation. The book begins with a review of icon research from various fields before laying a conceptual foundation that grounds the theory of the book. After and elaborating on that theory are chapters that demonstrate how to Establish Contexts to Guide Comprehension, Glean Which Symbols to Draw, Learn How to Draw Understandable Symbols, Clarify Metaphor, and Use Icons to Decipher Icons in Icon Systems. Written and carefully designed for a broad audience, the book's scholarly level is elevated while the presentation is approachable. Scholar or professional can skim, scan, or dig, it's up to them.Heavily illustrated and supported with ample citations, it is not only a book for students and professionals within the field of communication design, but also for anyone who communicates with visual symbols, from healthcare professionals to software engineers, affecting all kinds of graphic communications from advertisements to assembly instructions.
Agile Ehealth Usability Evaluation
The integration of usability evaluations into iterative software development processes is becoming increasingly relevant, as gathering feedback from prospective users is crucial to improving the usability of eHealth systems. Traditional approaches to eHealth usability evaluation, however, are difficult to reconcile with the iterative software development process, which is why there is an increasing need for agile usability evaluation. Despite the existence of approaches to agile usability evaluation, it is unclear whether they are suitable to rapidly evaluate patient-centered eHealth systems being iteratively developed in health care applicable, for prospective users such as elderly persons suffering from age-related declines. This research includes an innovative and comprehensive toolbox called ToUsE, toolbox for eHealth usability evaluation, which consists of more than 40 rapidly deployable and potentially useful eHealth usability evaluation methods developed by the author. The ToUsEtoolbox is intended for use by software developers, medical informaticians, usability experts, or medical professionals who aim at performing an eHealth usability evaluation. The book provides detailed descriptions of all the eHealth usability evaluation methods included in ToUsE.
Cracking the Data Science Interview
Rise above the competition and excel in your next interview with this one-stop guide to Python, SQL, version control, statistics, machine learning, and much moreKey FeaturesAcquire highly sought-after skills of the trade, including Python, SQL, statistics, and machine learningGain the confidence to explain complex statistical, machine learning, and deep learning theoryExtend your expertise beyond model development with version control, shell scripting, and model deployment fundamentalsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe data science job market is saturated with professionals of all backgrounds, including academics, researchers, bootcampers, and Massive Open Online Course (MOOC) graduates. This poses a challenge for companies seeking the best person to fill their roles. At the heart of this selection process is the data science interview, a crucial juncture that determines the best fit for both the candidate and the company.Cracking the Data Science Interview provides expert guidance on approaching the interview process with full preparation and confidence. Starting with an introduction to the modern data science landscape, you'll find tips on job hunting, resume writing, and creating a top-notch portfolio. You'll then advance to topics such as Python, SQL databases, Git, and productivity with shell scripting and Bash. Building on this foundation, you'll delve into the fundamentals of statistics, laying the groundwork for pre-modeling concepts, machine learning, deep learning, and generative AI. The book concludes by offering insights into how best to prepare for the intensive data science interview.By the end of this interview guide, you'll have gained the confidence, business acumen, and technical skills required to distinguish yourself within this competitive landscape and land your next data science job.What you will learnExplore data science trends, job demands, and potential career pathsSecure interviews with industry-standard resume and portfolio tipsPractice data manipulation with Python and SQLLearn about supervised and unsupervised machine learning modelsMaster deep learning components such as backpropagation and activation functionsEnhance your productivity by implementing code versioning through GitStreamline workflows using shell scripting for increased efficiencyWho this book is forWhether you're a seasoned professional who needs to brush up on technical skills or a beginner looking to enter the dynamic data science industry, this book is for you. To get the most out of this book, basic knowledge of Python, SQL, and statistics is necessary. However, anyone familiar with other analytical languages, such as R, will also find value in this resource as it helps you revisit critical data science concepts like SQL, Git, statistics, and deep learning, guiding you to crack through data science interviews.Table of ContentsExploring the Modern Data Science LandscapeFinding a Job in Data ScienceProgramming with PythonVisualizing Data and Data StorytellingQuerying Databases with SQLScripting with Shell and Bash Commands in LinuxUsing Git for Version ControlMining Data with Probability and StatisticsUnderstanding Feature Engineering and Preparing Data for ModelingMastering Machine Learning ConceptsBuilding Networks with Deep LearningImplementing Machine Learning Solutions with MLOpsMastering the Interview RoundsNegotiating Compensation
SQL Data Analytics Made Easy
Untangle the mesh of complex data with this user-friendly manual to SQLImagine a world overflowing with data - numbers, stats, facts, all buzzing around, waiting to tell a story. And you are in the middle of it all, seeking to make sense of this information whirlwind. Perhaps you're a professional trying to unlock new opportunities, a student aiming to stand out in the competitive job market, or simply just a curious individual fascinated by the power of data. Whichever it is, there's one common element that can help you navigate this vast sea of data - Structured Query Language (SQL). Think of it as your magical compass, guiding you to reveal the hidden treasures within data. SQL is not just a computer language - it's the bridge between you and valuable insights that can boost your career, enhance your studies, or even just satisfy your curiosity.The thought of stepping into this journey may feel daunting. You might be looking at this data ocean, wondering how you're ever going to make sense of it all. That's where exactly what this book is all about.This guide is all about turning what seems complex into something remarkably simple, replacing confusion with crystal-clear clarity, and answering the countless questions you've likely been struggling with.It's time to decode the complexities of data with SQL and evolve into a data wizard. Stop watching from the shoreline and dive into the data sea as you read this book, where inside you'll discover: The foundational principles of data analytics and the instrumental role of SQL - knowing the basics is the first step to success!Practical, hands-on exercises that will transition you from SQL novice to confident practitioner - level your skills up with every flip of this book's pagesProven techniques for data cleaning and integration using SQL (the secret ingredient behind sound data analysis)Advanced SQL queries to dig deep into data and extract meaningful insights - arrive at better and more reliable resultsHow to conduct robust statistical analyses using SQL... from hypothesis testing to regression analysis The art of creating compelling visualizations from SQL data - turn raw numbers into powerful storiesReal-world case studies that highlight the practical applications of SQL in various industriesAnd much more!Think SQL is too complex for you? Don't worry... this guide is designed to take you from the basics to advanced topics, regardless of your technical background.If you're concerned about practical applications, the book is laced with hands-on exercises to make sure you can apply the lessons immediately. Even better, there's no need to worry about evolving trends - SQL is a timeless skill, and this guide includes the latest advancements.So, what are you waiting for?It's time for data to make sense: Scroll up and click "Add to Cart" right now.
Data Warehousing
Introducing the "Data Warehousing: Optimizing Data Storage and Retrieval for Business Success" bundle!Unlock the full potential of your data with this comprehensive collection of four essential books: 1. Data Warehousing Fundamentals: A Beginner's Guide- Dive into the foundational principles of data warehousing and learn how to build a solid framework for storing and managing your organization's data.- Understand the importance of data modeling and gain insights into the extraction, transformation, and loading (ETL) processes essential for efficient data management.2. Mastering Data Modeling for Data Warehousing- Take your data modeling skills to the next level with advanced techniques for conceptual, logical, and dimensional modeling.- Learn how to design scalable and efficient data warehouses that meet the evolving needs of your organization.3. Advanced ETL Techniques for Data Warehousing Optimization- Optimize your ETL processes and streamline data extraction, transformation, and loading for maximum efficiency.- Explore advanced techniques such as incremental loading and change data capture (CDC) to ensure the smooth operation of your data warehouse.4. Big Data Analytics: Harnessing the Power of Data Warehousing for Experts- Unlock the transformative potential of big data analytics and gain actionable insights to drive informed decision-making.- Discover how to leverage your data warehouse for real-time data processing, predictive modeling, and more.With this bundle, you'll gain the knowledge and skills needed to optimize your data storage and retrieval processes, empowering you to harness the power of data for business success. Whether you're a beginner looking to build a solid foundation or an expert seeking advanced strategies, this bundle has something for everyone. Don't miss out on this opportunity to revolutionize your approach to data warehousing and take your business to new heights!
Technologies and Applications of Artificial Intelligence
This book constitutes the proceedings of the 28th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2023, which was held in Yunlin, Taiwan, during December 1-2, 2023. `The 35 full papers and 12 short papers included in this book were carefully reviewed and selected from 193 submissions. The TAAI 2023 provides a platform for experts and scholars from domestic and international universities, research units, and industries to exchange AI technologies and application results.
Information Systems
This book constitutes selected papers from the 20th European, Mediterranean, and Middle Eastern Conference, EMCIS 2023, which was held in Dubai, UAE, during December 11-12, 2023. EMCIS covers technical, organizational, business, and social issues in the application of information technology and is dedicated to the definition and establishment of Information Systems (IS) as a discipline of high impact for IS professionals and practitioners. It focuses on approaches that facilitate the identification of innovative research of significant relevance to the IS discipline following sound research methodologies that lead to results of measurable impact. The 43 papers presented in this volume were carefully reviewed and selected from a total of 126 submissions. They were organized in topical sections as follows: Part I: Metaverse; blockchain technology and applications; digital governance; healthcare information systems; artificial intelligence; Part II: Big data and analytics; digital services and social media; innovative research projects; managing information systems; smart cities.
Advances in Information Retrieval
The six-volume set LNCS 14608, 14609, 14609, 14610, 14611, 14612 and 14613 constitutes the refereed proceedings of the 46th European Conference on IR Research, ECIR 2024, held in Glasgow, UK, during March 24-28, 2024.The 57 full papers, 18 finding papers, 36 short papers, 26 IR4Good papers, 18 demonstration papers, 9 reproducibility papers, 8 doctoral consortium papers, and 15 invited CLEF papers were carefully reviewed and selected from 578 submissions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.
Advances in Information Retrieval
The six-volume set LNCS 14608, 14609, 14609, 14610, 14611, 14612 and 14613 constitutes the refereed proceedings of the 46th European Conference on IR Research, ECIR 2024, held in Glasgow, UK, during March 24-28, 2024.The 57 full papers, 18 finding papers, 36 short papers, 26 IR4Good papers, 18 demonstration papers, 9 reproducibility papers, 8 doctoral consortium papers, and 15 invited CLEF papers were carefully reviewed and selected from 578 submissions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.
Passive and Active Measurement
This book constitutes the proceedings of the 25th International Conference on Passive and Active Measurement, PAM 2024, held as a virtual event from March 11-13, 2024.The 14 full papers and 13 short papers presented in this volume were carefully reviewed and selected from 64 submissions. The papers are organized in the following topical sections: Applications, IPv6, Machine Learning, and Measurement Tools.
Cognitive Social Mining Applications in Data Analytics and Forensics
Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.
Process Mining Workshops
This volume constitutes the revised selected papers of several workshops which were held in conjunction with the 5th International Conference on Process Mining, ICPM 2023, held in Rome, Italy, in October 23-27, 2023.The 38 revised full papers presented in this book were carefully reviewed and selected from 85 submissions. The book also contains one invited talk. ICPM 2023 presented the following six workshops: - 4th International Workshop on Event Data and Behavioral Analytics (EdbA)- 4th International Workshop on Leveraging Machine Learning in Process Mining (ML4PM)- 6th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H)- 8th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI)- 2nd International Workshop on Education Meets Process Mining (EduPM)- 2nd International Workshop on Collaboration Mining for Distributed Systems (COMINDS).
Passive and Active Measurement
This book constitutes the proceedings of the 25th International Conference on Passive and Active Measurement, PAM 2024, held as a virtual event from March 11-13, 2024.The 14 full papers and 13 short papers presented in this volume were carefully reviewed and selected from 64 submissions. The papers are organized in the following topical sections: Network Security, Routing, Satellite Networks, Topology, Transport Protocol and User Privacy.
Technologies and Applications of Artificial Intelligence
This book constitutes the proceedings of the 28th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2023, which was held in Yunlin, Taiwan, during December 1-2, 2023.The 35 full papers and 12 short papers included in this book were carefully reviewed and selected from 193 submissions. The TAAI 2023 provides a platform for experts and scholars from domestic and international universities, research units, and industries to exchange AI technologies and application results.
Advances in Information Retrieval
The six-volume set LNCS 14608, 14609, 14609, 14610, 14611, 14612 and 14613 constitutes the refereed proceedings of the 46th European Conference on IR Research, ECIR 2024, held in Glasgow, UK, during March 24-28, 2024.The 57 full papers, 18 finding papers, 36 short papers, 26 IR4Good papers, 18 demonstration papers, 9 reproducibility papers, 8 doctoral consortium papers, and 15 invited CLEF papers were carefully reviewed and selected from 578 submissions. The accepted papers cover the state of the art in information retrieval focusing on user aspects, system and foundational aspects, machine learning, applications, evaluation, new social and technical challenges, and other topics of direct or indirect relevance to search.
Power BI
Unlock the Full Potential of Your Data with the "Power BI Data Mastery Made Easy" Book Bundle!Are you ready to transform your data into actionable insights and make informed decisions that drive success? Look no further! Introducing the "Power BI Data Mastery Made Easy" book bundle, a comprehensive collection of resources that will empower you to harness the true power of Microsoft's leading business intelligence and data visualization tool-Power BI.Here's what you'll discover in this incredible bundle: Book 1 - Power BI Essentials: A Beginner's Guide to Data Visualization Mastery- Ideal for beginners: Build a solid foundation in data visualization.- Learn to import and transform data from various sources.- Master the art of data analysis and visualization.Book 2 - Mastering Power BI: Advanced Techniques and Best Practices for Analysts- Elevate your skills to the next level with advanced techniques.- Discover best practices for tackling complex analytical challenges.- Master DAX formulas and optimize data models.- Become an analytics expert and excel in your field.Book 3 - Power BI Data Modeling: Building Robust Datasets for Effective Analysis- Unlock the full potential of Power BI with robust data modeling.- Design efficient and flexible data models.- Gain the skills to create powerful data sets for effective analysis.Book 4 - Expert Power BI: Advanced Analytics and Custom Visualizations Mastery- Dive into the world of advanced analytics and custom visuals.- Explore machine learning integration and geographic analysis.- Become a Power BI expert and stand out in your field.Grab the "Power BI Data Mastery Made Easy" book bundle today and start your exciting adventure into the world of Power BI-where data mastery is within reach for everyone!
SQL Data Analytics Made Easy
Untangle the mesh of complex data with this user-friendly manual to SQLImagine a world overflowing with data - numbers, stats, facts, all buzzing around, waiting to tell a story. And you are in the middle of it all, seeking to make sense of this information whirlwind. Perhaps you're a professional trying to unlock new opportunities, a student aiming to stand out in the competitive job market, or simply just a curious individual fascinated by the power of data. Whichever it is, there's one common element that can help you navigate this vast sea of data - Structured Query Language (SQL). Think of it as your magical compass, guiding you to reveal the hidden treasures within data. SQL is not just a computer language - it's the bridge between you and valuable insights that can boost your career, enhance your studies, or even just satisfy your curiosity.The thought of stepping into this journey may feel daunting. You might be looking at this data ocean, wondering how you're ever going to make sense of it all. That's where exactly what this book is all about.This guide is all about turning what seems complex into something remarkably simple, replacing confusion with crystal-clear clarity, and answering the countless questions you've likely been struggling with.It's time to decode the complexities of data with SQL and evolve into a data wizard. Stop watching from the shoreline and dive into the data sea as you read this book, where inside you'll discover: The foundational principles of data analytics and the instrumental role of SQL - knowing the basics is the first step to success!Practical, hands-on exercises that will transition you from SQL novice to confident practitioner - level your skills up with every flip of this book's pagesProven techniques for data cleaning and integration using SQL (the secret ingredient behind sound data analysis)Advanced SQL queries to dig deep into data and extract meaningful insights - arrive at better and more reliable resultsHow to conduct robust statistical analyses using SQL... from hypothesis testing to regression analysis The art of creating compelling visualizations from SQL data - turn raw numbers into powerful storiesReal-world case studies that highlight the practical applications of SQL in various industriesAnd much more!Think SQL is too complex for you? Don't worry... this guide is designed to take you from the basics to advanced topics, regardless of your technical background.If you're concerned about practical applications, the book is laced with hands-on exercises to make sure you can apply the lessons immediately. Even better, there's no need to worry about evolving trends - SQL is a timeless skill, and this guide includes the latest advancements.So, what are you waiting for?It's time for data to make sense: Scroll up and click "Add to Cart" right now.
Building Interactive Dashboards in Microsoft 365 Excel
Unleash the full potential of Microsoft Excel's latest version and elevate your data-driven prowess with this comprehensive resourceKey Features- Create robust and automated dashboards in Excel for M365- Apply data visualization principles and employ dynamic charts and tables to create constantly updated and informative dashboards for your organization- Uncover the best practices for effective dashboard creation- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionM365 Excel is a modern Excel version that is constantly updated with features that make creating and automating analyses, reports, and dashboards very easy compared with older Excel versions. This book will help you leverage its full capabilities, beginning with a quick overview of what dashboards are and how they are different from other types of reports. Then, you'll familiarize yourself with the different standard dashboards currently available and what they are meant to accomplish for organizations. As you progress, you'll get to grips with the use of new powerful tools such as Power Query and dynamic array formulae in the automation of analysis, gaining insights into the right approach to take in building effective dashboards. You'll equip yourself with not only all the essential formulae, charts, and non-chart visuals but also learn how to set up your dashboard perfectly. Along the way, you'll build a couple of awesome dashboards from scratch to utilize your newfound knowledge.By the end of this book, you will be able to carry out an impressive and robust level of analysis on business data that may come from multiple sources or files, using better processes, formulae, and best practices in M365 to create insightful dashboards faster.What you will learn- Understand the importance of dashboards in today's business analytics environment- Delve into the various essential formulae in Excel- Utilize Power Query to shape and transform data to extract insights easily- Explore the power of the new dynamic array functions in M365- Employ PivotTable and Power Pivot to automate your dashboards- Master the setup and optimization of your dashboard canvas- Discover best practices for visualization, charts, and effective dashboard creation- Consolidate your knowledge through a hands-on concluding projectWho this book is forThis book is for Microsoft Excel users, especially those tasked with creating dynamic reports and dashboards that require data and help support to decision-makers within an organization with visually engaging and actionable insights. Financial analysts, data analysts, business analysts, and BI professionals will also greatly benefit from this book. Some familiarity with the Microsoft Excel interface is a prerequisite.Table of Contents- Dashboards, Reports, and M365 Excel- Common Dashboards in Large Companies- The Importance of Connecting Directly to the Primary Data Sources- Power Query: the Ultimate Data Transformation Tool- PivotTable and Power Pivot- Must-Know Legacy Excel Functions- Dynamic Array Functions and Lambda Functions- Getting Comfortable with the 19 Excel Charts- Non-Chart Visuals- Setting Up the Dashboard's Data Model- Perfecting the Dashboard- Best Practices for Real-World Dashboard Building
Economic Terms in the News During the Great Recession
This book explores the evolution of sentiment in economic terms in the press during financial crises applying a combination of sentiment analysis techniques and usage fluctuation analysis on a diachronic corpus derived from editorials in quality newspapers during the Great Recession. The book uncovers two key findings: first, certain economic terms become event words during times of crisis due to their increased use in the press and the general public, revealing rapid semantic changes in economic terms caused by major socio-economic events. Second, sentiment-laden collocations are found to be influenced by culture, highlighting language's adaptability to financial upheavals. This work proposes an innovative methodology that combines lexicon-based Sentiment Analysis, Corpus Linguistics, and qualitative Discourse Analysis to shed light on how language shapes economic discourse, making it a valuable resource for scholars exploring the relationship between language and historic events.
Digital Transformation
Digital Transformation in Industry 4.0/5.0 requires the effective and efficient application of digitalization technologies in the area of production systems. This book elaborates on concepts, techniques, and technologies from computer science in the context of Industry 4.0/5.0 and demonstrates their possible applications. Thus, the book serves as an orientation but also as a reference work for experts in the field of Industry 4.0/5.0 to successfully advance digitization in their companies.
Autodesk Vault Professional 2024
The Autodesk(R) Vault Professional 2024: Administrator Essentials guide introduces Autodesk Vault Professional 2024 to CAD administrators. The focus of this learning guide is to teach administrators how to set up and manage categories, lifecycles, revisions, file naming schemes, items, bills of materials (BOMs), and the engineering change order (ECO) process.This guide is intended for administrators with some knowledge of Autodesk Vault Professional's data management capabilities. The hands-on practices included in this guide reinforce usage of items, BOM and ECO features, and automated workflows. Topics CoveredIntroduction to Autodesk Vault ProfessionalManaging CategoriesLifecycle ManagementRevision ManagementFile Naming SchemesWorking with ItemsManaging ChangeWorking with Bills of MaterialsAdministering Autodesk Vault ProfessionalReportingThin Client PrerequisitesAccess to the 2024 version of the software, to ensure compatibility with this guide. Future software updates that are released by Autodesk may include changes that are not reflected in this guide. The practices and files included with this guide might not be compatible with prior versions (e.g., 2023).A good working knowledge of Autodesk CAD programs and working knowledge of Autodesk Vault Basic and Autodesk Vault document management features.
Mastering MongoDB 7.0 - Fourth Edition
Gain MongoDB expertise and discover advanced queries and Atlas insights with this ultimate guide to version 7.0Key Features: Enhance your proficiency in advanced queries, aggregation, and optimized indexing to achieve peak MongoDB performanceMonitor, back up, and integrate applications effortlessly with MongoDB AtlasImplement security thorough RBAC, auditing, and encryption to ensure comprehensive data protection and privacyPurchase of the print or Kindle book includes a free PDF eBookBook Description: Mastering MongoDB 7.0 explores the latest version of MongoDB, an exceptional NoSQL database solution that aligns with the needs of modern web applications. This book starts with an informative overview of MongoDB's architecture and developer tools, guiding you through the process of connecting to databases seamlessly.This MongoDB book explores advanced queries in detail, including aggregation pipelines and multi-document ACID transactions. It delves into the capabilities of the MongoDB Atlas developer data platform and the latest features, such as Atlas Vector Search, and their role in AI applications, enabling developers to build applications with the scalability and performance that today's organizations need. It also covers the creation of resilient search functionality using MongoDB Atlas Search. Mastering MongoDB 7.0's deep coverage of advanced techniques encompasses everything from role-based access control (RBAC) to user management, auditing practices, and encryption across data, network, and storage layers.By the end of this book, you'll have developed the skills necessary to create efficient, secure, and high-performing applications using MongoDB. You'll have the confidence to undertake complex queries, integrate robust applications, and ensure data security to overcome modern data challenges.What You Will Learn: Execute advanced MongoDB queries for intricate data insightsHarness the power of aggregation pipelines to transform dataEnsure data integrity with multi-document ACID transactionsOptimize query performance using strategic indexing techniquesNavigate MongoDB Atlas seamlessly for monitoring and backupsEnable robust search functionality with Atlas SearchMaster RBAC, user management, and data encryption for securityImplement auditing practices for transparency and accountabilityWho this book is for: This book is for developers with an intermediate skill level who aim to become MongoDB experts. Working knowledge of MongoDB is recommended to gain the most from this guide. Ideal for database administrators, app developers, and software engineers, this book will assist you in developing advanced skills to conquer intricate data tasks.
Applied Machine Learning and Data Analytics
This book constitutes the refereed conference proceedings of the 6th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2023, held in L羹beck, Germany, during November 9-10, 2023.The 17 full papers and 2 short papers presented in this book were carefully reviewed and selected from 76 submissions. The main conference AMLDA 2023 is renowned for presenting cutting-edge research on all aspects of machine learning as well as important application areas such as healthcare and medical imaging informatics, biometrics, forensics, precision agriculture, risk management, robotics, and satellite imaging.
Ubiquitous Security
This book constitutes the proceedings of the Third International Conference, UbiSec 2023, held in Exeter, UK, during November 1-3, 2023.The 29 full papers were carefully reviewed and selected from 91 submissions. They were organized in following topical sections: Cyberspace Security, Cyberspace Privacy, Cyberspace Anonymity
Data Warehouse and Data Mining
Data warehouse and data mining are essential technologies in the field of data analysis and business intelligence. Data warehouse provides a centralized repository of structured data and facilitates data storage and retrieval. Data mining, on the other hand, utilizes various algorithms and techniques to extract valuable patterns, trends, and insights from large datasets. The book explains the ins and outs of data warehousing by discussing its principles, benefits, and components, differentiating it from traditional databases. The readers will explore warehouse architecture, learn to navigate OLTP and OLAP systems, grasping the crux of the difference between ROLAP and MOLAP. The book is designed to help you discover data mining secrets with techniques like classification and clustering. You will be able to advance your skills by handling multimedia, time series, and text, staying ahead in the evolving data mining landscape.
The Ultimate Power Query Cookbook for Power Bi and Excel
Novice or expert, learn to simplify and optimize data transformationsDESCRIPTION "The Ultimate Power Query Cookbook for Power BI and Excel" serves up easy-to-follow recipes that transform data into meaningful insights. You will learn to clean messy files, combine datasets, and even use AI magic to Power BI and Excel.This book will walk you through the basics of getting connected to data with Power Query. You will understand how to ingest data from files, folders, databases, websites, APIs, and other third party sources. Once connected, you will learn how to transform the data so it is ready for your use. We will clean up columns, filter, replace, extract, and classify data in Power Query to meet your needs. The book offers over 100 practical recipes, ensuring you understand each step with clear explanations and examples. Lastly, we will go over advanced techniques to help optimize and simplify your transformations allowing fast refreshes all while helping you manage them in the future.This book will help you know how to apply these techniques and recipes to your data all while understanding the implications of making certain decisions. This will enable you to have better conversations with other data professionals who are providing data for your use.WHAT YOU WILL LEARN● Learn to connect to files, databases, and third-party services.● Manage data types and formats to optimize storage.● Transform, create, and manipulate queries.● Combine, merge, filter, and cleanse queries.● Integrate artificial intelligence to accelerate insights.● Perform complex and scalable transformations.WHO THIS BOOK IS FORNovice or expert, this book is designed for all Excel users, data analysts, Power BI power users, business professionals and data enthusiasts to get the most out of your data solutions when transforming your data in Power Query.
Chatbot Research and Design
This book constitutes the proceedings of the 7th International Workshop on Chatbot Research and Design, CONVERSATIONS 2023, which was held during November 2023.The 12 regular papers were carefully reviewed and selected for inclusion in the book. They were organized in following topical sections: Understanding and Enhancing Conversational Interactions, LLM-driven Conversational Design and Analysis, Ethical Perspectives and Bias, Complementing Perspectives.
Service-Oriented Computing - Icsoc 2023 Workshops
This book constitutes revised selected papers from the scientific satellite events held in conjunction with the 21st International Conference on Service-Oriented Computing, ICSOC 2023. The conference was held in Rome, Italy, during November 28 - December 1, 2023.This year, these satellite events were organized around four main tracks, including a workshop track, a demonstration track, a Ph.D. symposium, and an invited tutorial track.The ICSOC 2023 workshop track consisted of the following six workshops covering a wide range of topics that fall into the general area of service computing: Third International Workshop on AI-Enabled Process Automation (AI-PA 2023)7th Workshop on Adaptive Service-Oriented and Cloud Applications (ASOCA2023)First International Workshop on Secure, Accountable and Privacy-Preserving Data-Driven Service-Oriented Computing (SAPD 2023)First Services and Quantum Software Workshop (SQS 2023)First International Workshop on Sustainable Service-Oriented Computing: Addressing Environmental, Social, and Economic Dimensions (SSCOPE 2023) 19th International Workshop on Engineering Service-Oriented Applications and Cloud Services (WESOACS 2023)
Analysis of Images, Social Networks and Texts
This book constitutes revised selected papers from the thoroughly refereed proceedings of the 11th International Conference on Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023. The 24 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: natural language processing; computer vision; data analysis and machine learning; network analysis; and theoretical machine learning and optimization. The book also contains one invited talk in full paper length.
MATLAB for Machine Learning - Second Edition
Master MATLAB tools for creating machine learning applications through effective code writing, guided by practical examples showcasing the versatility of machine learning in real-world applicationsKey FeaturesWork with the MATLAB Machine Learning Toolbox to implement a variety of machine learning algorithmsEvaluate, deploy, and operationalize your custom models, incorporating bias detection and pipeline monitoringUncover effective approaches to deep learning for computer vision, time series analysis, and forecastingPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDiscover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications.By navigating the versatile machine learning tools in the MATLAB environment, you'll learn how to seamlessly interact with the workspace. You'll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you'll explore various classification and regression techniques, skillfully applying them with MATLAB functions.This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You'll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you'll leverage MATLAB tools for deep learning and managing convolutional neural networks.By the end of the book, you'll be able to put it all together by applying major machine learning algorithms in real-world scenarios.What you will learnDiscover different ways to transform data into valuable insightsExplore the different types of regression techniquesGrasp the basics of classification through Naive Bayes and decision treesUse clustering to group data based on similarity measuresPerform data fitting, pattern recognition, and cluster analysisImplement feature selection and extraction for dimensionality reductionHarness MATLAB tools for deep learning explorationWho this book is forThis book is for ML engineers, data scientists, DL engineers, and CV/NLP engineers who want to use MATLAB for machine learning and deep learning. A fundamental understanding of programming concepts is necessary to get started.Table of ContentsExploring MATLAB for Machine LearningWorking with Data in MATLABPrediction Using Classification and RegressionClustering Analysis and Dimensionality ReductionIntroducing Artificial Neural Networks ModelingDeep Learning and Convolutional Neural NetworksNatural Language Processing Using MATLABMATLAB for Image Processing and Computer VisionTime Series Analysis and Forecasting with MATLABMATLAB Tools for Recommender SystemsAnomaly Detection in MATLAB
Data Engineering with Scala and Spark
Take your data engineering skills to the next level by learning how to utilize Scala and functional programming to create continuous and scheduled pipelines that ingest, transform, and aggregate dataKey FeaturesTransform data into a clean and trusted source of information for your organization using ScalaBuild streaming and batch-processing pipelines with step-by-step explanationsImplement and orchestrate your pipelines by following CI/CD best practices and test-driven development (TDD)Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionMost data engineers know that performance issues in a distributed computing environment can easily lead to issues impacting the overall efficiency and effectiveness of data engineering tasks. While Python remains a popular choice for data engineering due to its ease of use, Scala shines in scenarios where the performance of distributed data processing is paramount. This book will teach you how to leverage the Scala programming language on the Spark framework and use the latest cloud technologies to build continuous and triggered data pipelines. You'll do this by setting up a data engineering environment for local development and scalable distributed cloud deployments using data engineering best practices, test-driven development, and CI/CD. You'll also get to grips with DataFrame API, Dataset API, and Spark SQL API and its use. Data profiling and quality in Scala will also be covered, alongside techniques for orchestrating and performance tuning your end-to-end pipelines to deliver data to your end users. By the end of this book, you will be able to build streaming and batch data pipelines using Scala while following software engineering best practices.What you will learnSet up your development environment to build pipelines in ScalaGet to grips with polymorphic functions, type parameterization, and Scala implicitsUse Spark DataFrames, Datasets, and Spark SQL with ScalaRead and write data to object storesProfile and clean your data using DeequPerformance tune your data pipelines using ScalaWho this book is forThis book is for data engineers who have experience in working with data and want to understand how to transform raw data into a clean, trusted, and valuable source of information for their organization using Scala and the latest cloud technologies. Table of ContentsScala Essentials for Data EngineersEnvironment SetupAn Introduction to Apache Spark and Its APIs - DataFrame, Dataset, and Spark SQLWorking with DatabasesObject Stores and Data LakesUnderstanding Data TransformationData Profiling and Data QualityTest-Driven Development, Code Health, and MaintainabilityCI/CD with GitHubData Pipeline OrchestrationPerformance TuningBuilding Batch Pipelines Using Spark and ScalaBuilding Streaming Pipelines Using Spark and Scala
100 Livestreaming & Digital Media Predictions, Volume 4
WINNER OF 21 BOOK AWARDSIn the ever-evolving digital media landscape, where Artificial Intelligence (AI) reshapes creativity and connection, "100 Livestreaming & Digital Media Predictions, Volume 4" emerges as your essential guide. Compiled by Ross Brand, an on-air personality and consultant for leading live video brands, this latest volume in our award-winning series (with 25 book awards to its name) is more than just a collection of predictions; it's a roadmap to mastering the digital realm in 2024 and beyond. Within these pages, 113 expert contributors, including Emmy winners, renowned YouTube influencers and Hall of Fame podcasters, share their foresight. They delve into how AI is redefining content creation, offering both foundational advice and groundbreaking strategies. From exploring AI's role in enhancing productivity to addressing fears of losing authenticity, this book tackles the pressing questions every creator and entrepreneur faces: What are the essential tools to integrate AI into your work?How can AI be leveraged to maximize efficiency without sacrificing creativity?What are the pitfalls of AI in digital media, and how can you navigate them?How can you maintain a genuine connection with your audience in an AI-driven world?"100 Livestreaming & Digital Media Predictions, Volume 4" isn't just a window into the future; it's a treasure trove of insights from industry leaders. You'll find exclusive predictions that shed light on emerging trends and practical pathways to navigate the complex interplay of AI and human creativity. Whether you're a seasoned creator or just starting, this book equips you with the knowledge to thrive in the dynamic digital media frontier. Critics and peers alike praise the "100 Predictions" series for its depth, accuracy and utility. As the fourth installment, this volume continues the tradition of excellence, offering a unique blend of expert opinions and actionable advice. Embark on a journey through the converging paths of AI and human ingenuity. Let the insights of seasoned experts arm you with the tools to not just anticipate the future but to shape it. GET IT NOW and be part of the vanguard shaping the digital media landscape in 2024 and beyond.
Principles of Data Science - Third Edition
Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your dataKey FeaturesLearn practical data science combined with data theory to gain maximum insights from dataDiscover methods for deploying actionable machine learning pipelines while mitigating biases in data and modelsExplore actionable case studies to put your new skills to use immediatelyPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionPrinciples of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights.Starting with cleaning and preparation, you'll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you'll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data.With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You'll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you'll explore medium-level data governance, including data provenance, privacy, and deletion request handling.By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.What you will learnMaster the fundamentals steps of data science through practical examplesBridge the gap between math and programming using advanced statistics and MLHarness probability, calculus, and models for effective data controlExplore transformative modern ML with large language modelsEvaluate ML success with impactful metrics and MLOpsCreate compelling visuals that convey actionable insightsQuantify and mitigate biases in data and ML modelsWho this book is forIf you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. Whether you have basic math skills and want to apply them in the field of data science, or you excel in programming but lack the necessary mathematical foundations, you'll find this book useful. Familiarity with Python programming will further enhance your learning experience.Table of ContentsData Science TerminologyTypes of DataThe Five Steps of Data ScienceBasic MathematicsImpossible or Improbable - A Gentle Introduction to ProbabilityAdvanced ProbabilityWhat are the Chances? An Introduction to StatisticsAdvanced StatisticsCommunicating Data How to Tell if Your Toaster is Learning - Machine Learning EssentialsPredictions Don't Grow on Trees, or Do They?Introduction to Transfer Learning and Pre-trained ModelsMitigating Algorithmic Bias and Tackling Model and Data DriftAI GovernanceNavigating Real-World Data Science Case Studies in Action
Applied Intelligence
This 2-volume set CCIS 2014 and CCIS 2015 constitutes the post-conference proceedings of the First International Conference on Applied Intelligence, ICAI 2023, held in Nanning, China, December 8-12, 2023.The 64 full papers presented in this proceedings were carefully selected and reviewed from 228 submissions. The papers cover a wide range on theoretical aspects of biomedical data modeling and mining; computer vision; and deep learning. They were organized in topical sections as follows: Part I: Biomedical data modeling and mining; computer vision; deep learning; Part II: Intelligent control and automation; machine learning; natural language processing and computational linguistics.
