Data Science
This three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27-30, 2024. The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions. The papers are organized in the following topical sections: Part I: Novel methods or tools used in big data and its applications; applications of data science. Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management. Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
Data Science
This three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27-30, 2024. The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions. The papers are organized in the following topical sections: Part I: Novel methods or tools used in big data and its applications; applications of data science. Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management. Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
Machine Learning and Metaheuristic Computation
Learn to bridge the gap between machine learning and metaheuristic methods to solve problems in optimization approaches Few areas of technology have greater potential to revolutionize the globe than artificial intelligence. Two key areas of artificial intelligence, machine learning and metaheuristic computation, have an enormous range of individual and combined applications in computer science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both. Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge artificial intelligence tools. The text also provides: Treatment suitable for readers with only basic mathematical training Detailed discussion of topics including dimensionality reduction, clustering methods, differential evolution, and more A rigorous but accessible vision of machine learning algorithms and the most popular approaches of metaheuristic optimization Machine Learning and Metaheuristic Computation is ideal for students, researchers, and professionals looking to combine these vital methods to solve problems in optimization approaches.
Data Science
This three-volume set CCIS 2213-2215 constitutes the refereed proceedings of the 10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024, held in Macau, China, during September 27-30, 2024. The 74 full papers and 3 short papers presented in these three volumes were carefully reviewed and selected from 249 submissions. The papers are organized in the following topical sections: Part I: Novel methods or tools used in big data and its applications; applications of data science. Part II: Education research, methods and materials for data science and engine; data security and privacy; big data mining and knowledge management. Part III: Infrastructure for data science; social media and recommendation system; multimedia data management and analysis.
Subject-Oriented Business Process Management. Models for Designing Digital Transformations
This book constitutes the refereed post proceedings of the 15th International Conference on Subject-Oriented Business Process Management, S-BPM ONE 2024, held in Weiden, Germany, during May 21-22, 2024. The 14 full papers and 8 short papers included in this book were carefully reviewed and selected from 30 submissions. These papers have been organized in the following topical sections: Processes And Data; Subject-Oriented Modeling, Philosophy, and Technology; Processes and Sustainability; Good Process Practices.
Data Quality Management in the Data Age
This book addresses data quality management for data markets, including foundational quality issues in modern data science. By clarifying the concept of data quality, its impact on real-world applications, and the challenges stemming from poor data quality, it will equip data scientists and engineers with advanced skills in data quality management, with a particular focus on applications within data markets. This will help them create an environment that encourages potential data sellers with high-quality data to join the market, ultimately leading to an improvement in overall data quality. High-quality data, as a novel factor of production, has assumed a pivotal role in driving digital economic development. The acquisition of such data is particularly important for contemporary decision-making models. Data markets facilitate the procurement of high-quality data and thereby enhance the data supply. Consequently, potential data sellers with high-quality data are incentivized to enter the market, an aspect that is particularly relevant in data-scarce domains such as personalized medicine and services. Data scientists have a pivotal role to play in both the intellectual vitality and the practical utility of high-quality data. Moreover, data quality control presents opportunities for data scientists to engage with less structured or ambiguous problems. The book will foster fruitful discussions on the contributions that various scientists and engineers can make to data quality and the further evolution of data markets.
Pandas Cookbook - Third Edition
From fundamental techniques to advanced strategies for handling big data, visualization, and more, this book equips you with skills to excel in real-world data analysis projects.Key Features: - This book targets features in pandas 2.x and beyond- Practical, easy to implement recipes for quick solutions to common problems in data using pandas- Master the fundamentals of pandas to quickly begin exploring any datasetBook Description: The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter.With this latest edition unlock the full potential of pandas 2.x onwards. Whether you're a beginner or an experienced data analyst, this book offers a wealth of practical recipes to help you excel in your data analysis projects. This cookbook covers everything from fundamental data manipulation tasks to advanced techniques for handling big data, visualization, and more. Each recipe is designed to address common real-world challenges, providing clear explanations and step-by-step instructions to guide you through the process.Explore cutting-edge topics such as idiomatic pandas coding, efficient handling of large datasets, and advanced data visualization techniques.  Whether you're looking to sharpen or expand your skills, the "Pandas Cookbook" is your essential companion for mastering data analysis and manipulation with pandas 2.x, and beyond.What You Will Learn: - The pandas type system and how to best navigate it- Import/export DataFrames to/from common data formats- Data exploration in pandas through dozens of practice problems- Grouping, aggregation, transformation, reshaping, and filtering data- Merge data from different sources through pandas SQL-like operations- Leverage the robust pandas time series functionality in advanced analyses- Scale pandas operations to get the most out of your system- The large ecosystem that pandas can coordinate with and supplementWho this book is for: This book is for Python developers, data scientists, engineers, and analysts. pandas is the ideal tool for manipulating structured data with Python and this book provides ample instruction and examples. Not only does it cover the basics required to be proficient, but it goes into the details of idiomatic pandasTable of Contents- Pandas Foundations- Selection / Indexing- Pandas data types- Pandas Input/Output- Algorithms and how to apply them- Visualization- Reshaping Dataframes- Groupby- Temporal Data Types and Algorithms- Exploratory Data Analysis - The pandas ecosystem
Delta Lake: The Definitive Guide
Ready to simplify the process of building data lakehouses and data pipelines at scale? In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Prashanth Babu (with contributions from Delta Lake maintainer R. Tyler Croy) share expert insights on all things Delta Lake--including how to run batch and streaming jobs concurrently and accelerate the usability of your data. You'll also uncover how ACID transactions bring reliability to data lakehouses at scale. This book helps you: Understand key data reliability challenges and how Delta Lake solves them Explain the critical role of Delta transaction logs as a single source of truth Learn the Delta Lake ecosystem with technologies like Apache Flink, Kafka, and Trino Architect data lakehouses with the medallion architecture Optimize Delta Lake performance with features like deletion vectors and liquid clustering
Building Modern Data Applications Using Databricks Lakehouse
Get up to speed with the Databricks Data Intelligence Platform to build and scale modern data applications, leveraging the latest advancements in data engineeringKey Features: - Learn how to work with real-time data using Delta Live Tables- Unlock insights into the performance of data pipelines using Delta Live Tables- Apply your knowledge to Unity Catalog for robust data security and governance- Purchase of the print or Kindle book includes a free PDF eBookBook Description: With so many tools to choose from in today's data engineering development stack as well as operational complexity, this often overwhelms data engineers, causing them to spend less time gleaning value from their data and more time maintaining complex data pipelines. Guided by a lead specialist solutions architect at Databricks with 10+ years of experience in data and AI, this book shows you how the Delta Live Tables framework simplifies data pipeline development by allowing you to focus on defining input data sources, transformation logic, and output table destinations.This book gives you an overview of the Delta Lake format, the Databricks Data Intelligence Platform, and the Delta Live Tables framework. It teaches you how to apply data transformations by implementing the Databricks medallion architecture and continuously monitor the data quality of your pipelines. You'll learn how to handle incoming data using the Databricks Auto Loader feature and automate real-time data processing using Databricks workflows. You'll master how to recover from runtime errors automatically.By the end of this book, you'll be able to build a real-time data pipeline from scratch using Delta Live Tables, leverage CI/CD tools to deploy data pipeline changes automatically across deployment environments, and monitor, control, and optimize cloud costs.What You Will Learn: - Deploy near-real-time data pipelines in Databricks using Delta Live Tables- Orchestrate data pipelines using Databricks workflows- Implement data validation policies and monitor/quarantine bad data- Apply slowly changing dimensions (SCD), Type 1 and 2, data to lakehouse tables- Secure data access across different groups and users using Unity Catalog- Automate continuous data pipeline deployment by integrating Git with build tools such as Terraform and Databricks Asset BundlesWho this book is for: This book is for data engineers looking to streamline data ingestion, transformation, and orchestration tasks. Data analysts responsible for managing and processing lakehouse data for analysis, reporting, and visualization will also find this book beneficial. Additionally, DataOps/DevOps engineers will find this book helpful for automating the testing and deployment of data pipelines, optimizing table tasks, and tracking data lineage within the lakehouse. Beginner-level knowledge of Apache Spark and Python is needed to make the most out of this book.Table of Contents- An Introduction to Delta Live Tables- Applying Data Transformations Using Delta Live Tables- Managing Data Quality Using Delta Live Tables- Scaling DLT Pipelines- Mastering Data Governance in the Lakehouse with Unity Catalog- Managing Data Locations in Unity Catalog- Viewing Data Lineage Using Unity Catalog- Deploying, Maintaining, and Administrating DLT Pipelines Using Terraform- Leveraging Databricks Asset Bundles to Streamline Data Pipeline Deployment- Monitoring Data Pipelines in Production
Data Engineering in Medical Imaging
This book constitutes the proceedings of the Second MICCAI Workshop on Data Engineering in Medical Imaging, DEMI 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 10, 2024. The 18 papers presented in this book were carefully reviewed and selected. These papers focus on the application of various Data engineering techniques in the field of Medical Imaging.
Elements of Data Science
Elements of Data Science is an introduction to the practical skills of working with data, written for people with no programming experience. Concepts are explained clearly and concisely, and exercises in each chapter demonstrate the real-world use of each feature. * Step-by-Step Approach: Learn how to execute a data science project from start to finish, formulating questions, visualizing data, applying statistical methods, and communicating results. * Practical Python Programming: This book starts with basic Python concepts and builds up to advanced data processing and analysis techniques. * Interactive Learning: Jupyter notebooks are available for each chapter, so readers can follow along, run experiments, and build understanding through hands-on exercises. * Solid Foundation: Explore fundamental concepts such as exploratory data analysis, statistical inference, regression analysis, classification algorithms, and more, all through the lens of real-world case studies. Whether you're a student, a professional, or simply curious about the power of data, Elements of Data Science provides essential tools for finding insights in data.
Computer and Communication Engineering
This book constitutes the proceedings of the 4th International Conference on Computer and Communication Engineering, CCCE 2024, which took place in Oslo, Norway, during May 24-26, 2024. The 19 full papers included in this book were carefully reviewed and selected from 47 submissions. They are organized in topical sections as follows: Intelligent image analysis and multimedia technology; information network and security; digital communication and information systems; and design and implementation of modern information management systems.
Developing an Enterprise Continuity Program
This book will be useful to Chief Information Security Officers, internal and external Certified Information Systems Auditors, senior managers within companies who are responsible for ensuring business continuity and cyber stability, as well as teachers and students of MBA's, CIO and CSO programs.
Mastering Opentelemetry and Observability
Discover the power of open source observability for your enterprise environment In Mastering Observability and OpenTelemetry: Enhancing Application and Infrastructure Performance and Avoiding Outages, accomplished engineering leader and open source contributor Steve Flanders unlocks the secrets of enterprise application observability with a comprehensive guide to OpenTelemetry (OTel). Explore how OTel transforms observability, providing a robust toolkit for capturing and analyzing telemetry data across your environment. You will learn how OTel delivers unmatched flexibility, extensibility, and vendor neutrality, freeing you from vendor lock-in and enabling data sovereignty and portability. You will also discover: Comprehensive coverage of observability issues and technology: Dive deep into the world of observability and gain a comprehensive understanding of observability fundamentals with practical insights and real-world use cases. Practical guidance: From instrumentation techniques to advanced tracing strategies, gain the skills needed to create highly observable systems. Learn how to deploy and configure OTel, even in challenging brownfield environments, with step-by-step instructions and hands-on exercises. An opportunity for community contributions and communication: Join the OTel community, including end-users, vendors, and cloud providers, and shape the future of observability while connecting with experts and peers. Whether you are a novice or a seasoned professional, Mastering Observability and OpenTelemetry is your roadmap to troubleshooting availability and performance problems by learning to detect anomalies, interpret data, and proactively optimize performance in your enterprise environment. Embark on your journey to observability mastery today!
Advances in Computing and Data Sciences
This book constitutes the refereed proceedings of the 8th International Conference on Advances in Computing and Data Sciences, ICACDS 2024, held in Velizy, France, during May 9-10, 2024. The 28 full papers present here, were carefully reviewed and selected from 174 submissions. The papers focus on innovative research in the field of Advanced Computing and Data Sciences, including areas such as artificial intelligence, machine learning, big data analytics, cloud computing, computer vision and natural language processing.
Aerospike: Up and Running
If you're a developer looking to build a distributed, resilient, scalable, high-performance application, you may be evaluating distributed SQL and NoSQL solutions. Perhaps you're considering the Aerospike database. This practical book shows developers, architects, and engineers how to get the highly scalable and extremely low-latency Aerospike database up and running. You will learn how to power your globally distributed applications and take advantage of Aerospike's hybrid memory architecture with the real-time performance of in-memory plus dependable persistence. After reading this book, you'll be able to build applications that can process up to tens of millions of transactions per second for millions of concurrent users on any scale of data. This practical guide provides: Step-by-step instructions on installing and connecting to Aerospike A clear explanation of the programming models available All the advice you need to develop your Aerospike application Coverage of issues such as administration, connectors, consistency, and security Code examples and tutorials to get you up and running quickly And more
Apache Airflow Best Practices
Confidently orchestrate your data pipelines with Apache Airflow by applying industry best practices and scalable strategiesKey Features: - Understand the steps for migrating from Airflow 1.x to 2.x and explore the new features and improvements in version 2.x- Learn Apache Airflow workflow authoring through real-world use cases- Uncover strategies to operationalize your Airflow instance and pipelines for resilient operations and high throughput- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Data professionals face the monumental task of managing complex data pipelines, orchestrating workflows across diverse systems, and ensuring scalable, reliable data processing. This definitive guide to mastering Apache Airflow, written by experts in engineering, data strategy, and problem-solving across tech, financial, and life sciences industries, is your key to overcoming these challenges. It covers everything from the basics of Airflow and its core components to advanced topics such as custom plugin development, multi-tenancy, and cloud deployment.Starting with an introduction to data orchestration and the significant updates in Apache Airflow 2.0, this book takes you through the essentials of DAG authoring, managing Airflow components, and connecting to external data sources. Through real-world use cases, you'll gain practical insights into implementing ETL pipelines and machine learning workflows in your environment. You'll also learn how to deploy Airflow in cloud environments, tackle operational considerations for scaling, and apply best practices for CI/CD and monitoring.By the end of this book, you'll be proficient in operating and using Apache Airflow, authoring high-quality workflows in Python for your specific use cases, and making informed decisions crucial for production-ready implementation.What You Will Learn: - Explore the new features and improvements in Apache Airflow 2.0- Design and build data pipelines using DAGs- Implement ETL pipelines, ML workflows, and other advanced use cases- Develop and deploy custom plugins and UI extensions- Deploy and manage Apache Airflow in cloud environments such as AWS, GCP, and Azure- Describe a path for the scaling of your environment over time- Apply best practices for monitoring and maintaining AirflowWho this book is for: This book is for data engineers, developers, IT professionals, and data scientists who want to optimize workflow orchestration with Apache Airflow. It's perfect for those who recognize Airflow's potential and want to avoid common implementation pitfalls. Whether you're new to data, an experienced professional, or a manager seeking insights, this guide will support you. A functional understanding of Python, some business experience, and basic DevOps skills are helpful. While prior experience with Airflow is not required, it is beneficial.Table of Contents- Getting Started with Airflow 2.0- Core Airflow Concepts- Components of Airflow- Basics of Airflow and DAG Authoring- Connecting to External Sources- Extending Functionality with UI Plugins- Writing and Distributing Custom Providers- Orchestrating a Machine Learning Workflow- Using Airflow as a Driving Service- Airflow Ops: Development and Deployment- Airflow Ops Best Practices: Observation and Monitoring- Multi-Tenancy in Airflow- Migrating Airflow
From Zero to Hero in C# and C++
Don't miss a gorgeous and spellbinding romance set in beautiful Spain from bestselling author T.A. Williams, perfect for fans of Karen Swan, Carol Kirkwood and Fiona Valpy! Out of darkness, light will shine... Amy Hardy once lived a life full of colour, but a tragic accident has turned her world to shadows. Determined to embrace her new life, Amy sets off on the famous Compostela pilgrimage, hoping to find light in the darkness and a new path. Accompanying her on her journey is Luke Patterson a man whose own troubled past casts dark shadows over his life. He's hoping that guiding Amy will be a distraction from his own troubles. But as Luke and Amy travel through the stunning scenery of Northern Spain, following in footsteps of those travellers before them, they feel a connection to each other. And as their bond grows, a love story from the distant past emerges before them, forcing them to confront their own secrets, pain and feelings for each other. Can a story of courage and bravery help them both to emerge from the shadows into the light once more? Under A Spanish Sky is an enchanting novel about the search for happiness, fulfilment...and above all love. Please Note: This book was previously published as Chasing Shadows Readers love T.A.Williams 'Absolutely loved this novel like I do every other book by T.A. Williams. Loved the setting, the characters and the storyline.' ⭐⭐⭐⭐⭐ Reader review 'T. A. Williams has that gorgeous way of writing a feel good story and something which will easily make you smile... he's absolutely backed up that men can write chick-lit.' Reviewed The Book 'Fantastic story by an entertaining author!' Gilbster 'A superbly crafted, heartwarming tale' Splashes into Books 'I had my doubts as to whether a 'bloke' would get it! To get beneath the skin of a woman and process how she'd feel in various scenarios. Let's just say I don't have any longer - you nailed it.' Crooksonbooks
Advances on Graph-Based Approaches in Information Retrieval
This book constitutes the refereed proceedings of the First International Workshop on Graph-Based Approaches in Information Retrieval, IRonGraphs 2024, held in Glasgow, UK, on March 24, 2024. The 6 full papers included in this book were carefully reviewed and selected from 14 submissions. They focus on diverse novel contributions, with presentations on knowledge-aware graph-based recommender systems using user-based semantic features filtering, source-target node distance impacts on adversarial attacks in social network recommendations.
Applications of Artificial Intelligence, Big Data and Internet of Things in Sustainable Development
This book focuses on different algorithms and models related to AI, big data, and IoT used for various domains. It enables the reader to have a broader and deep understanding of several perspectives, about the dynamics, challenges, and opportunities regarding sustainable development using artificial intelligence, big data, and IoT.
PostgreSQL 17 QuickStart Pro
PostgreSQL 17 QuickStart Pro is the definitive hands-on, practical book for professionals at every level, from entry-level administrators to seasoned experts. It provides rapid learning and practical implementation of PostgreSQL 17, focusing on the latest features and best practices to effectively manage, configure, and optimize PostgreSQL databases-and it does so effectively.The book begins by using the Titanic dataset to illustrate practical examples of upgrade strategies, post-upgrade validation, and database configuration. Next, it covers cluster administration, configuration settings, and performance tracking. You will master the management of permissions and roles through intricate role hierarchies, authentication methods, and security settings. Next, we'll optimize server performance, plan queries, and manage resources based on real performance data.The next section dives deep into complicated data types, bulk data operations, advanced indexing methods, and the creation of triggers and functions, all with an emphasis on effective data management. Next, you will learn about table partitioning strategies, performing physical and logical backups, database restoration, and process automation using BART. We then move on to streaming replication, where we will configure, administer, and monitor replication to ensure optimal uptime. Finally, we will explore point-in-time recovery (PITR), which allows us to restore databases to specific points in time by replaying WAL logs. In short, this book will equip database administrators with the knowledge and skills to confidently handle PostgreSQL 17 databases.Key LearningsUpgrade and configure PostgreSQL 17, including post-upgrade validation and configuration.Learn PostgreSQL architecture, memory models, and cluster management.Use hierarchical permissions, authentication, and security for advanced role management.Tune server performance with query planning, resource management, and configuration tuning.Effectively use PostgreSQL extensions, JSONB, and arrays.Optimize queries with GIN, GiST, and BRIN indexing.Master table partitioning for large dataset performance and scalability.Automate physical and logical backups and confidently restore databases.Manage PostgreSQL streaming replication for high availability and automatic failover.Restore data using WAL logs and Point-in-Time Recovery.Table of ContentUpgrading and Setting up PostgreSQL 17Expert Database Cluster AdministrationAdvanced Database and Role ManagementConfiguration and Performance TuningEffective Data ManagementTable Partitioning StrategiesBackup and Recovery Best PracticesStreaming Replication and High AvailabilityPoint-in-Time Recovery
Simulation for a Sustainable Future
The two volume set CCIS 2032 and 2033 constitutes the proceedings of the 11th Congress on Simulation for a Sustainable Future, EUROSIM 2023, which was held in Amsterdam, The Netherlands, during July 3-5, 2023. The 47 full papers included in the proceedings were carefully reviewed and selected from 99 submissions. The papers are divided in the following topical sections: ​environmental sustainability; healthcare; production systems; business and industries; logistics and transportation systems; monitor, control, and theoretical systems.
Process Mining Techniques for Managing and Improving Healthcare Systems
This book discusses a new process mining method along with a detailed comparison between different techniques that provide a complete vision of the process of data acquisition, data analysis, and data prediction.
RAG-Driven Generative AI
Minimize AI hallucinations and build accurate, custom generative AI pipelines with RAG using embedded vector databases and integrated human feedbackGet With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader FreeKey Features: - Implement RAG's traceable outputs, linking each response to its source document to build reliable multimodal conversational agents- Deliver accurate generative AI models in pipelines integrating RAG, real-time human feedback improvements, and knowledge graphs- Balance cost and performance between dynamic retrieval datasets and fine-tuning static dataBook Description: RAG-Driven Generative AI provides a roadmap for building effective LLM, computer vision, and generative AI systems that balance performance and costs.This book offers a detailed exploration of RAG and how to design, manage, and control multimodal AI pipelines. By connecting outputs to traceable source documents, RAG improves output accuracy and contextual relevance, offering a dynamic approach to managing large volumes of information. This AI book shows you how to build a RAG framework, providing practical knowledge on vector stores, chunking, indexing, and ranking. You'll discover techniques to optimize your project's performance and better understand your data, including using adaptive RAG and human feedback to refine retrieval accuracy, balancing RAG with fine-tuning, implementing dynamic RAG to enhance real-time decision-making, and visualizing complex data with knowledge graphs.You'll be exposed to a hands-on blend of frameworks like LlamaIndex and Deep Lake, vector databases such as Pinecone and Chroma, and models from Hugging Face and OpenAI. By the end of this book, you will have acquired the skills to implement intelligent solutions, keeping you competitive in fields from production to customer service across any project.What You Will Learn: - Scale RAG pipelines to handle large datasets efficiently- Employ techniques that minimize hallucinations and ensure accurate responses- Implement indexing techniques to improve AI accuracy with traceable and transparent outputs- Customize and scale RAG-driven generative AI systems across domains- Find out how to use Deep Lake and Pinecone for efficient and fast data retrieval- Control and build robust generative AI systems grounded in real-world data- Combine text and image data for richer, more informative AI responsesWho this book is for: This book is ideal for data scientists, AI engineers, machine learning engineers, and MLOps engineers. If you are a solutions architect, software developer, product manager, or project manager looking to enhance the decision-making process of building RAG applications, then you'll find this book useful.Table of Contents- Why Retrieval Augmented Generation?- RAG Embedding Vector Stores with Deep Lake and OpenAI- Building Index-Based RAG with LlamaIndex, Deep Lake, and OpenAI- Multimodal Modular RAG for Drone Technology- Boosting RAG Performance with Expert Human Feedback- Scaling RAG Bank Customer Data with Pinecone- Building Scalable Knowledge-Graph-Based RAG with Wikipedia API and LlamaIndex- Dynamic RAG with Chroma and Hugging Face Llama- Empowering AI Models: Fine-Tuning RAG Data and Human Feedback- RAG for Video Stock Production with Pinecone and OpenAI
Data Engineering Best Practices
Explore modern data engineering techniques and best practices to build scalable, efficient, and future-proof data processing systems across cloud platformsKey Features: - Architect and engineer optimized data solutions in the cloud with best practices for performance and cost-effectiveness- Explore design patterns and use cases to balance roles, technology choices, and processes for a future-proof design- Learn from experts to avoid common pitfalls in data engineering projects- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Revolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines.You'll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you'll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications.By the end, you'll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.What You Will Learn: - Architect scalable data solutions within a well-architected framework- Implement agile software development processes tailored to your organization's needs- Design cloud-based data pipelines for analytics, machine learning, and AI-ready data products- Optimize data engineering capabilities to ensure performance and long-term business value- Apply best practices for data security, privacy, and compliance- Harness serverless computing and microservices to build resilient, scalable, and trustworthy data pipelinesWho this book is for: If you are a data engineer, ETL developer, or big data engineer who wants to master the principles and techniques of data engineering, this book is for you. A basic understanding of data engineering concepts, ETL processes, and big data technologies is expected. This book is also for professionals who want to explore advanced data engineering practices, including scalable data solutions, agile software development, and cloud-based data processing pipelines.Table of Contents- Overview of the Business Problem Statement- A Data Engineer's Journey - Background Challenges- A Data Engineer's Journey - IT's Vision and Mission- Architecture Principles- Architecture Framework - Conceptual Architecture Best Practices- Architecture Framework - Logical Architecture Best Practices- Architecture Framework - Physical Architecture Best Practices- Software Engineering Best Practice Considerations- Key Considerations for Agile SDLC Best Practices- Key Considerations for Quality Testing Best Practices- Key Considerations for IT Operational Service Best Practices(N.B. Please use the Read Sample option to see further chapters)
Ultimate Data Science Programming in Python
DESCRIPTION In today's data-driven world, the ability to extract meaningful insights from vast datasets is crucial for success in various fields. This ultimate book for mastering open-source libraries of data science in Python equips you with the essential tools and techniques to navigate the ever-evolving field of data analysis and visualization.Discover how to use Python libraries like NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization. This book also covers scientific computing with SciPy and integrates ChatGPT to boost your data science workflow. Designed for data scientists, analysts, and beginners, it offers a practical, hands-on approach to mastering data science fundamentals. With real-world applications and exercises, you will turn raw data into actionable insights, gaining a competitive edge. This book covers everything you need, including open-source libraries, Visual Explorer tools, and ChatGPT, making it a one-stop resource for Python-based data science.Readers will gain confidence after going through this book and we assure you that all the minute details have been taken into consideration while delivering the content. After reading, learning, and practicing from this book, we are sure that all IT professionals, novices, or job seekers will be able to work on data science projects thus proving their mettle.WHAT YOU WILL LEARN● Learn to work with popular IDEs like VS Code and Jupyter Notebook for efficient Python development.● Master open-source libraries such as NumPy, SciPy, Matplotlib, and Pandas through advanced, real-world examples.● Utilize automated EDA tools like PyGWalker and AutoViz to simplify complex data analysis.● Create sophisticated visualizations like heatmaps, FacetGrid, and box plots using Matplotlib and Seaborn.● Efficiently handle missing data, outliers, and perform filtering, sorting, grouping, and aggregation using Pandas and Polars.WHO THIS BOOK IS FORThis book is ideal for diploma, undergraduate, and postgraduate students from engineering and science fields to programming and software professionals. It is also perfect for data science, ML, and AI engineers looking to expand their expertise in cutting-edge technologies.
Cockroachdb: The Definitive Guide
Get the lowdown on CockroachDB, the distributed SQL database built to handle the demands of today's data-driven cloud applications. In the second edition of this popular hands-on guide, software developers, architects, and DevOps/SRE teams will learn how to use CockroachDB to create applications that scale elastically and provide seamless delivery for end users while remaining indestructible. Data engineers and database administrators will also learn how to migrate existing applications to CockroachDB's performant, cloud native data architecture. If you're familiar with distributed systems, you'll quickly discover the benefits of strong data correctness and consistency guarantees, as well as optimizations for delivering ultra-low latencies to globally distributed end users. You'll learn how to: Examine the power of and need for distributed SQL and distributed architecture, and their impact on unparalleled resilience Successfully start and manage a project in CockroachDB Design and build applications for distributed infrastructure, including data modeling and schema design Migrate data into CockroachDB Read and write data and run ACID transactions across distributed infrastructure Plan a CockroachDB deployment for resiliency across and multiregion clusters Secure, monitor, and optimize your CockroachDB deployment
MySQL 8 Cookbook
For database developers, administrators, engineers, and backend developers, MySQL 8 Cookbook provides solution-focused recipes. This book takes a practical approach to solving real-world problems by showing readers how to increase database security, enhance performance, and fix common MySQL issues through the use of numerous examples.You will learn how to install, configure, and tune MySQL for optimal performance in Linux environments. Important topics like backup strategies, security measures, query optimization, high availability, and replication are covered in each chapter. You will learn to partition and index datasets in a way that improves query performance, and the book provides step-by-step solutions to help them manage big datasets. With the help of this book, you can convert MySQL into a schema-less database that can manage unstructured data with ease, and it even handles modern data types like JSON. You can build fault-tolerant and scalable database systems including the implementation of multi-source replication, master-slave replication, and master-master replication.Problems like table corruption, excessive CPU and memory usage, deadlocks, and replication lag are addressed in the troubleshooting sections. Also shown are methods for automating and monitoring database security using Linux tools, cron jobs, and MySQL's performance schema. Whether you're managing enterprise databases or developing backend applications, this book will teach you to improve your database management skills and ensure peak performance for systems that are critical to business.Key LearningsDiscover the ins and outs of installing, configuring, and optimizing MySQL 8 for high-performance database systems.Maximize database availability by implementing advanced replication setups, including master-master and multi-source.Take advantage of partitioning and indexing techniques to efficiently manage massive datasets and improve query performance.Use MySQL's relational and NoSQL features in combination to manage dynamic and schema-less data using JSON support.Use cron jobs and Linux-native tools to automate backups, recovery, and security audits.Find the cause of MySQL problems like table corruption, deadlocks, and replication lag and fix them.Implement strong firewall settings, encryption, and user access control to protect your MySQL environment.Use memory tuning and full-text search indexing to optimize MySQL performance and speed up queries.Use MySQL's performance schema in conjunction with Linux tools to keep an eye on system performance and resource usage.Table of ContentInstalling and Configuring MySQL 8Optimizing MySQL Architecture and Storage EnginesSecuring MySQLOptimizing Queries and PerformanceConfiguring MySQL ReplicationEnhancing MySQL High AvailabilityAutomating MySQL Maintenance and UpdatesAdvanced MySQL Troubleshooting and DebuggingMonitoring and Tuning MySQL Performance
IoT and Big Data Analytics for Smart Cities
The book emphasizes the challenges, architectural models, intelligent frameworks with smart decision- making systems using Big Data and IoT with case studies. The book illustrates the benefits of Big Data and IoT methods in framing smart systems for smart applications.
Semantic Web Technologies
This book provides a roadmap for Semantic Web Technologies (SWTs) and highlights their role in wide range of domains including Cloud Computing, IoT, Big data, Sensor Network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations.
Big Data Analytics in Smart Manufacturing
The ultra-secure and immutable ledgers, strong, consensus mechanisms, decentralization, and self-sovereign identity of AI and IoT technologies have tremendous potential to rebalance and improve machine learning algorithms. This book discusses the possibility of using AI, IoT and machine learning for the enhancement of healthcare systems.
Synergistic Interaction of Big Data with Cloud Computing for Industry 4.0
The goal of this book is to help aspiring readers and researchers understand the convergence of Big Data with the Cloud. This book presents the latest information on the adaptation and implementation of Big Data technologies in various cloud domains and Industry 4.0.
Machine Learning, Deep Learning, Big Data, and Internet of Things for Healthcare
This book discusses the various machine learning, deep learning, big data and internet of things technologies for healthcare. The book is primarily aimed at graduates and researchers studying emerging technologies in healthcare. Industry and medical professionals will also find this book helpful.
Digital Future of Healthcare
This book focusses on applications of different digital platforms in the field of healthcare including different devices used, their benefits, diagnosis, use in treatment, and use cases related to mobile healthcare. It covers machine learning, blockchain technology, big data analytics digital healthcare, telehealth technology and so forth.
Computational Intelligence and Data Sciences
This book presents futuristic trends in computational intelligence including algorithms used in different application domains in health informatics covering bio-medical, bioinformatics, &biological sciences. It provides conceptual framework with a focus on computational intelligence techniques in biomedical engineering &health informatics.
Cancer Prediction for Industrial IoT 4.0
This book presents the developments in machine learning with data mining, and their influence in Industrial IoT 4.0 for cancer prediction. It is aimed primarily at graduates and researchers working in machine learning and data mining. Researchers and healthcare specialists studying cancer will also find this book useful.
Trust, Security and Privacy for Big Data
The book provides timely and comprehensive information for researchers and industry partners in communications and networking domains to review the latest results in security and privacy related work of big data.
Healthcare 4.0
The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes, Informatics involved by applying the data, information and knowledge in the healthcare domain.
Statistical Trend Analysis of Physically Unclonable Functions
Statistical Trend Analysis of Physically Unclonable Functions first presents a review on cryptographic hardware and hardware-assisted cryptography. Afterwards, the authors present a combined survey and research work on PUFs using a systematic approach.
Big Data Analytics
This book includes various topics related to marketing and business analytics. It is written to help organizations increase their profits by making better decisions. This book is meant for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce, marketing, and big data analytics.
Machine Learning and IoT for Intelligent Systems and Smart Applications
This book discusses algorithmic applications in the field of machine learning and IOT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. It includes pertinent applications and case studies.
Oracle Database Programming with Java
This textbook provides a detailed description about the practical considerations and applications in Oracle database programming using the most updated Apache NetBeans 12.4. Combined with real examples, this book gives students a clear picture as how to handle the Oracle database programming issues in Java NetBeans IDE environment.
Data Driven Decision Making using Analytics
This book aims to build and prompt the field of Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focussed on specific issues, including concepts of Database Technology, Machine learning, Knowledge-based system, High Performance Computing etc.
Smart Computational Intelligence in Biomedical and Health Informatics
Smart Computational Intelligence in Biomedical and Health Informatics presents state-of-art innovations, research, design and implementation of methodological and algorithmic solutions to data processing problems, designing, and analysing evolving trends in health informatics and computer-aided diagnosis.
Computing Technologies and Applications
The book focuses on suggesting software solutions for supporting societal issues such as health care, learning and monitoring mythology for disables and also technical solutions for better living. It also has the high potential to be used as recommended textbook for research scholars and post-graduate programs.
Data Analytics for Pandemics
The focus of this book is data analytics for COVID-19 which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussion on data models, their performance, different Big data techniques, tools and technologies.
