Skybook_IT 📖

📕 Mastering PostgreSQL 17 Elevate your database skills with advanced deployment, optimization, and security strategies 🔘Edited by: Hans-Jürgen Schönig 🔘Paperback : 474 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. What is New in PostgreSQL 17 2. Understanding Transactions and Locking 3. Making Use of Indexes 4. Handling Advanced SQL 5. Log Files and System Statistics 6. Optimizing Queries for Good Performance 7. Writing Stored Procedures 8. Managing PostgreSQL Security 9. Handling Backup and Recovery 10. Making Sense of Backups and Replication 11. Deciding on Useful Extensions 12. Troubleshooting PostgreSQL 13. Migrating to PostgreSQL Starting with new features introduced in PostgreSQL 17, the sixth edition of this book provides comprehensive insights into advanced database management, helping you elevate your PostgreSQL skills to an expert level. Written by Hans-Jürgen Schönig, a PostgreSQL expert with over 25 years of experience and the CEO of CYBERTEC PostgreSQL International GmbH, this guide distills real-world expertise from supporting countless global customers. It guides you through crucial aspects of professional database management, including performance tuning, replication, indexing, and security strategies. You’ll learn how to handle complex queries, optimize execution plans, and enhance user interactions with advanced SQL features such as window functions and JSON support. Hans equips you with practical approaches for managing database locks, transactions, and stored procedures to ensure peak performance. With real-world examples and expert solutions, you'll also explore replication techniques for high availability, along with troubleshooting methods to detect and resolve bottlenecks, preparing you to tackle everyday challenges in database administration.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Real-World Web Development with .NET 9 Build websites and services using mature and proven ASP.NET Core MVC, Web API, and Umbraco CMS 🔘Edited by: Mark J. Price 🔘Paperback : 579 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Introducing Web Development Using Controllers 2. Building Websites Using ASP.NET Core MVC 3. Model Binding, Validation, and Data Using EF Core 4. Building and Localizing Web User Interfaces 5. Authentication and Authorization 6. Performance Optimization Using Caching 7. Web User Interface Testing Using Playwright 8. Configuring and Containerizing ASP.NET Core Projects 9. Building Web Services Using ASP.NET Core Web API 10. Building Web Services Using ASP.NET Core OData 11. Building Web Services Using FastEndpoints 12. Web Service Integration Testing 13. Web Content Management Using Umbraco 14. Customizing and Extending Umbraco Real-World Web Development with .NET 9 equips you to build professional websites and services using proven technologies like ASP.NET Core MVC, Web API, and OData—trusted by organizations for delivering robust web applications. You’ll learn to design and build efficient web applications with ASP.NET Core MVC, creating well-structured, maintainable code that follows industry best practices. From there, you’ll focus on Web API, building RESTful services that are both secure and scalable. Along the way, you’ll also explore testing, authentication, and containerization for deployment, ensuring that your solutions are fully production ready. In the final part of the book, you will be introduced to Umbraco CMS, a popular content management system for .NET. By mastering this tool, you’ll learn how to empower users to manage website content independently. By the end of this book, you'll not only have a solid grasp of controller-based development but also the practical know-how to build dynamic, content-driven websites using a popular .NET CMS.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Modern C++ Programming Cookbook Master Modern C++ with comprehensive solutions for C++23 and all previous standards 🔘Edited by: Soledad Galli 🔘Paperback : 817 pages (B5) 🔘Edition : 3 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Learning Modern Core Language Features 2. Working with Numbers and Strings 3. Exploring Functions 4. Preprocessing and Compilation 5. Standard Library Containers, Algorithms, and Iterators 6. General-Purpose Utilities 7. Working with Files and Streams 8. Leveraging Threading and Concurrency 9. Robustness and Performance 10. Implementing Patterns and Idioms 11. Exploring Testing Frameworks 12. C++23 Features The updated third edition of Modern C++ Programming Cookbook addresses the latest features of C++23, such as the stack library, the expected and mdspan types, span buffers, formatting library improvements, and updates to the ranges library. It also gets into more C++20 topics not previously covered, such as sync output streams and source_location The book is organized into practical recipes covering a wide range of real-world problems, helping you find the solutions you need quickly. You’ll find coverage of all the core concepts of modern C++ programming and features and techniques from C++11 through to C++23, meaning you’ll stay ahead of the curve by learning to incorporate the newest language and library improvements Beyond the core concepts and new features, you’ll explore recipes related to performance and best practices, how to implement useful patterns and idioms, like pimpl, named parameter, attorney-client, and the factory pattern, and how to complete unit testing with the widely used C++ libraries: Boost.Test, Google Test, and Catch2 With the comprehensive coverage this C++ programming guide offers, by the end of the book you’ll have everything you need to build performant, scalable, and efficient applications in C++.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Python Feature Engineering Cookbook A complete guide to crafting powerful features for your machine learning models 🔘Edited by: Soledad Galli 🔘Paperback : 396 pages (B5) 🔘Edition : 3 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Imputing Missing Data 2. Encoding Categorical Variables 3. Transforming Numerical Variables 4. Performing Variable Discretization 5. Working with Outliers 6. Extracting Features from Date and Time Variables 7. Performing Feature Scaling 8. Creating New Features 9. Extracting Features from Relational Data with Featuretools 10. Creating Features from a Time Series with tsfresh 11. Extracting Features from Text Variables Streamline data preprocessing and feature engineering in your machine learning project with this third edition of the Python Feature Engineering Cookbook to make your data preparation more efficient. This guide addresses common challenges, such as imputing missing values and encoding categorical variables using practical solutions and open source Python libraries. You’ll learn advanced techniques for transforming numerical variables, discretizing variables, and dealing with outliers. Each chapter offers step-by-step instructions and real-world examples, helping you understand when and how to apply various transformations for well-prepared data. The book explores feature extraction from complex data types such as dates, times, and text. You’ll see how to create new features through mathematical operations and decision trees and use advanced tools like Featuretools and tsfresh to extract features from relational data and time series. By the end, you’ll be ready to build reproducible feature engineering pipelines that can be easily deployed into production, optimizing data preprocessing workflows and enhancing machine learning model performance.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Hands-On Blockchain for Python Developers Empowering Python developers in the world of blockchain and smart contracts 🔘Edited by: Arjuna Sky Kok 🔘Paperback : 436 pages (B5) 🔘Edition : 2 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

Part 1: Blockchain and Smart Contract 1. Chapter 1: Introduction to Blockchain Programming 2. Chapter 2: Smart Contract Fundamentals 3. Chapter 3: Using Vyper to Implement a Smart Contract Part 2: Web3 and Ape Framework 4. Chapter 4: Using Web3.py to Interact with Smart Contracts 5. Chapter 5: Ape Framework 6. Chapter 6: Building a Practical Decentralized Application Part 3: Graphical User Interface Applications 7. Chapter 7: Front-End Decentralized Application 8. Chapter 8: Cryptocurrency Wallet Part 4: Related Technologies 9. Chapter 9: InterPlanetary: A Brave New File System 10. Chapter 10: Implementing a Decentralized Application Using IPFS 11. Chapter 11: Exploring Layer 2 Part 5: Cryptocurrency and NFT 12. Chapter 12: Creating Tokens on Ethereum 13. Chapter 13: How to Create an NFT Part 6: Writing Complex Smart Contracts 14. Chapter 14: Writing NFT Marketplace Smart Contracts 15. Chapter 15: Writing a Lending Vault Smart Contract 16. Chapter 16: Decentralized Exchange Part 7: Building a Full-Stack Web3 Application 17. Chapter 17: Token-Gated Applications We are living in the age of decentralized fi nance and NFTs. People swap tokens on Uniswap, borrow assets from Aave, send payments with stablecoins, trade art NFTs on OpenSea, and more. To build applications of this kind, you need to know how to write smart contracts. This comprehensive guide will help you explore all the features of Vyper, a programming language designed to write smart contracts. You'll also explore the web3.py library. As you progress, you'll learn how to connect to smart contracts, read values, and create transactions. To make sure your foundational knowledge is strong enough, the book guides you through Ape Framework, which can help you create decentralized exchanges, NFT marketplaces, voting applications, and more. Each project provides invaluable insights and hands-on experience, equipping you with the skills you need to build real-world blockchain solutions. By the end of this book, you'll be well versed with writing common Web3 applications such as a decentralized exchange, an NFT marketplace, a voting application, and more.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 LLM Engineer's Handbook Master the art of engineering large language models from concept to production 🔘Edited by: Paul Iusztin, Maxime Labonne 🔘Paperback : 532 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Understanding the LLM Twin Concept and Architecture 2. Tooling and Installation 3. Data Engineering 4. RAG Feature Pipeline 5. Supervised Fine-tuning 6. Fine-tuning with Preference Alignment 7. Evaluating LLMs 8. Inference Optimization 9. RAG Inference Pipeline 10. Inference Pipeline Deployment 11. MLOps and LLMOps 12. Appendix: MLOps Principles This LLM book provides practical insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps' best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter Notebooks, focusing on how to build production-grade end-to-end LLM systems. Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 AI Engineering Building Applications with Foundation Models 🔘Edited by: Chip Huyen 🔘Paperback : 532 pages (B5) 🔘Edition : 1 🔘Year : 2025 🔘Publisher : O'Reilly 📝 Contents & Book Description:

Chapter 1. Introduction to Building AI Applications with Foundation Models Chapter 2. Understanding Foundation Models Chapter 3. Evaluation Methodology Chapter 4. Evaluate AI Systems Chapter 5. Prompt Engineering Chapter 6. RAG and Agents Chapter 7. Finetuning Chapter 8. Dataset Engineering Chapter 9. Inference Optimization Chapter 10. AI Engineering Architecture and User Feedback Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products. The model-as-a-service approach has transformed AI from an esoteric discipline into a powerful development tool that anyone can use. Everyone, including those with minimal or no prior AI experience, can now leverage AI models to build applications. In this book, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models. The book starts with an overview of AI engineering, explaining how it differs from traditional ML engineering and discussing the new AI stack. The more AI is used, the more opportunities there are for catastrophic failures, and therefore, the more important evaluation becomes. This book discusses different approaches to evaluating open-ended models, including the rapidly growing AI-as-a-judge approach. AI application developers will discover how to navigate the AI landscape, including models, datasets, evaluation benchmarks, and the seemingly infinite number of use cases and application patterns. You'll learn a framework for developing an AI application, starting with simple techniques and progressing toward more sophisticated methods, and discover how to efficiently deploy these applications.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

☺️ کتاب Designing Distributed Systems به ویرایش دوم به‌روز رسانی شد. هر Distributed Systems برای اطمینان، عملکرد و کیفیت تلاش می‌کند، اما ساخت چنین سیستمی سخت است. ایجاد مجموعه‌ای از دیزاین پترن‌ها، دولوپرها و آرشیتکت‌ها را قادر می‌سازد تا از یک زبان مشترک برای توصیف سیستم‌های خود استفاده کنند و از الگوها و شیوه‌های توسعه یافته توسط دیگران بیاموزند. محبوبیت کانتینرها و Kubernetes راه را برای Core Distributed System و اجزای کانتینری قابل استفاده مجدد هموار می‌کند. این راهنمای عملی مجموعه‌ای از الگوهای تکرارپذیر و عمومی را ارائه می‌کند تا به راهنمایی سیستم‌هایی که با استفاده از الگوها و شیوه‌های رایج می‌سازید، از برخی از Distributed Systems با بالاترین عملکرد که امروزه استفاده می‌شوند، کمک کند. با این الگوهای رایج سیستم‌هایی را که می‌سازید بسیار قابل دسترس‌تر و کارآمدتر می‌کنند، حتی اگر قبلاً هرگز تجربه ساخت یک Distributed Systems نداشته‌اید. 👁 مشاهده فهرست و تعدادی از صفحات 🟡 خرید از سایت: 🔗 https://skybooks.ir/products/Designing-Distributed-Systems

📕 Designing Distributed Systems Patterns and Paradigms for Scalable, Reliable Systems Using Kubernetes 🔘Edited by: Brendan Burns 🔘Paperback : 220 pages (B5) 🔘Edition : 2 🔘Year : 2025 🔘Publisher : O'Reilly 📝 Contents & Book Description:

Part I. Foundational Concepts Chapter 1. Introduction Chapter 2. Important Distributed System Concepts Part II. Single-Node Patterns Chapter 3. The Sidecar Pattern Chapter 4. Ambassadors Chapter 5. Adapters Part III. Serving Patterns Chapter 6. Replicated Load-Balanced Services Chapter 7. Sharded Services Chapter 8. Scatter/Gather Chapter 9. Functions and Event-Driven Processing Chapter 10. Ownership Election Part IV. Batch Computational Patterns Chapter 11. Work Queue Systems Chapter 12. Event-Driven Batch Processing Chapter 13. Coordinated Batch Processing Part V. Universal Concepts Chapter 14. Monitoring and Observability Patterns Chapter 15. AI Inference and Serving Chapter 16. Common Failure Patterns Every distributed system strives for reliability, performance, and quality, but building such a system is hard. Establishing a set of design patterns enables software developers and system architects to use a common language to describe their systems and learn from the patterns and practices developed by others. The popularity of containers and Kubernetes paves the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help guide the systems you build using common patterns and practices drawn from some of the highest performing distributed systems in use today. These common patterns make the systems you build far more approachable and efficient, even if you've never built a distributed system before. Author Brendan Burns demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. This fully updated second edition includes new chapters on AI inference, AI training, and building robust systems for the real world.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Duckdb: Up and Running Fast Data Analytics and Reporting 🔘Edited by: Wei-Meng Lee 🔘Paperback : 308 pages (B5) 🔘Edition : 1 🔘Year : 2025 🔘Publisher : O'Reilly 📝 Contents & Book Description:

Chapter 1. Getting Started with DuckDB Chapter 2. Importing Data into DuckDB Chapter 3. A Primer on SQL Chapter 4. Using DuckDB with Polars Chapter 5. Performing EDA with DuckDB Chapter 6. Using DuckDB with JSON Files Chapter 7. Using DuckDB with JupySQL Chapter 8. Accessing Remote Data Using DuckDB Chapter 9. Using DuckDB in the Cloud with MotherDuck DuckDB, an open source in-process database created for OLAP workloads, provides key advantages over more mainstream OLAP solutions: It's embeddable and optimized for analytics. It also integrates well with Python and is compatible with SQL, giving you the performance and flexibility of SQL right within your Python environment. This handy guide shows you how to get started with this versatile and powerful tool. Author Wei-Meng Lee takes developers and data professionals through DuckDB's primary features and functions, best practices, and practical examples of how you can use DuckDB for a variety of data analytics tasks. You'll also dive into specific topics, including how to import data into DuckDB, work with tables, perform exploratory data analysis, visualize data, perform spatial analysis, and use DuckDB with JSON files, Polars, and JupySQL.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Delta Lake: The Definitive Guide Modern Data Lakehouse Architectures with Data Lakes 🔘Edited by: Denny Lee, Tristen Wentling, Scott Haines, and Prashanth Babu 🔘Paperback : 383 pages (B5) 🔘Edition : 1 🔘Year : 2025 🔘Publisher : O'Reilly 📝 Contents & Book Description:

Chapter 1. Introduction to the Delta Lake Lakehouse Format Chapter 2. Installing Delta Lake Chapter 3. Essential Delta Lake Operations Chapter 4. Diving into the Delta Lake Ecosystem Chapter 5. Maintaining Your Delta Lake Chapter 6. Building Native Applications with Delta Lake Chapter 7. Streaming In and Out of Your Delta Lake Chapter 8. Advanced Features Chapter 9. Architecting Your Lakehouse Chapter 10. Performance Tuning: Optimizing Your Data Pipelines with Delta Lake Chapter 11. Successful Design Patterns Chapter 12. Foundations of Lakehouse Governance and Security Chapter 13. Metadata Management, Data Flow, and Lineage Chapter 14. Data Sharing with the Delta Sharing Protocol 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.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Test-Driven React Find Problems Early, Fix Them Quickly, Code with Confidence 🔘Edited by: Trevor Burnham 🔘Paperback : 170 pages (B5) 🔘Edition : 2 🔘Year : 2024 🔘Publisher : Pragmatic Bookshelf 📝 Contents & Book Description:

1. Test-Driven Development with Jest 2. Integrated Tooling with VS Code 3. Testing React with Testing Library 4. Styling in JavaScript with Styled-Components 5. Refactoring with Hooks 6. Continuous Integration and Collaboration Turn your React project requirements into tests and get the feedback you need faster than ever before. Combine the power of testing, linting, and typechecking directly in your coding environment to iterate on React components quickly and fearlessly! You work in a loop: write code, get feedback, adjust. The faster you get feedback, the faster your code improves and the more effective you become as a developer. And that feedback comes from testing. The conceptual elegance of React has opened the door to a new generation of web testing: clear, expressive, and lightning fast. That makes React a perfect fit for test-driven development (TDD), a methodology in which tests are a blueprint instead of an afterthought.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Outlier Detection in Python 🔘Edited by: Brett Kennedy 🔘Paperback : 562 pages (B5) 🔘Edition : 1 🔘Year : 2025 🔘Publisher : Manning 📝 Contents & Book Description:

Part 1 1 Introducing outlier detection 2 Simple outlier detection 3 Machine learning-based outlier detection 4 The outlier detection process Part 2 5 Outlier detection using scikit-learn 6 The PyOD library 7 Additional libraries and algorithms for outlier detection Part 3 8 Evaluating detectors and parameters 9 Working with specific data types 10 Handling very large and very small datasets 11 Synthetic data for outlier detection 12 Collective outliers 13 Explainable outlier detection 14 Ensembles of outlier detectors 15 Working with outlier detection predictions Outliers can be the most informative parts of your data, revealing hidden insights, novel patterns, and potential problems. For a business, this can mean finding new products, expanding markets, and flagging fraud or other suspicious activity. Outlier Detection in Python introduces the tools and techniques you'll need to uncover the parts of a dataset that don't look like the rest, even when they're the more hidden or intertwined among the expected bits.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Logs and Telemetry Using Fluent Bit, Kubernetes, streaming and more 🔘Edited by: Phil Wilkins 🔘Paperback : 394 pages (B5) 🔘Edition : 1 🔘Year : 2025 🔘Publisher : Manning 📝 Contents & Book Description:

PART 1. From concepts to running Fluent Bit 1. Introduction to Fluent Bit 2. From zero to “Hello, World” PART 2. Digging deeper 3. Capturing inputs 4 . Getting inputs from containers and Kubernetes 5. Outputting events 6. Parsing to extract more meaning 7. Filtering and transforming events PART 3. Plugins and queries 8. Stream processors for time series calculations and filtering 9. Building processors and Fluent Bit extension options 10. Building plugins 11. Putting Fluent Bit into action: An enterprise use case Build cloud native observability pipelines with minimal footprints and high-performance throughput―all with Fluent Bit, Kubernetes, and your favorite visualization and analytics tools. Logs and Telemetry is an all-practical guide to monitoring both cloud-native and traditional environments with the Fluent Bit observability tool. It takes you from the basics of collecting app logs, all the way to filtering, routing, enriching and transforming logs, metrics, and traces.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 In-Memory Analytics with Apache Arrow Accelerate data analytics for efficient processing of flat and hierarchical data structures 🔘Edited by: Matthew Topol 🔘Paperback : 406 pages (B5) 🔘Edition : 2 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Getting Started with Apache Arrow 2. Working with Key Arrow Specifications 3. Format and Memory Handling 4. Crossing the Language Barrier with the Arrow C Data API 5. Acero: A Streaming Arrow Execution Engine 6. Using the Arrow Datasets API 7. Exploring Apache Arrow Flight RPC 8. Understanding Arrow Database Connectivity (ADBC) 9. Using Arrow with Machine Learning Workflows 10. Powered by Apache Arrow 11. How to Leave Your Mark on Arrow 12. Future Development and Plans Apache Arrow is an open source, columnar in-memory data format designed for efficient data processing and analytics. This book harnesses the author’s 15 years of experience to show you a standardized way to work with tabular data across various programming languages and environments, enabling high-performance data processing and exchange. This updated second edition gives you an overview of the Arrow format, highlighting its versatility and benefits through real-world use cases. It guides you through enhancing data science workflows, optimizing performance with Apache Parquet and Spark, and ensuring seamless data translation. You’ll explore data interchange and storage formats, and Arrow's relationships with Parquet, Protocol Buffers, FlatBuffers, JSON, and CSV. You’ll also discover Apache Arrow subprojects, including Flight, SQL, Database Connectivity, and nanoarrow. You’ll learn to streamline machine learning workflows, use Arrow Dataset APIs, and integrate with popular analytical data systems such as Snowflake, Dremio, and DuckDB. The latter chapters provide real-world examples and case studies of products powered by Apache Arrow, providing practical insights into its applications. By the end of this book, you’ll have all the building blocks to create efficient and powerful analytical services and utilities with Apache Arrow.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Apache Airflow Best Practices A practical guide to orchestrating data workflow with Apache Airflow 🔘Edited by: Dylan Intorf, Dylan Storey, Kendrick van Doorn 🔘Paperback : 188 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Getting Started with Airflow 2.0 2. Core Airflow Concepts 3. Components of Airflow 4. Basics of Airflow and DAG Authoring 5. Connecting to External Sources 6. Extending Functionality with UI Plugins 7. Writing and Distributing Custom Providers 8. Orchestrating a Machine Learning Workflow 9. Using Airflow as a Driving Service 10. Airflow Ops: Development and Deployment 11. Airflow Ops Best Practices: Observation and Monitoring 12. Multi-Tenancy in Airflow 13. Migrating Airflow 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.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Biostatistics with Python Apply Python for biostatistics with hands-on biomedical and biotechnology projects 🔘Edited by: Darko Medin 🔘Paperback : 374 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

Part I: Introduction to Biostatistics and Getting Started with Python Chapter 1 : Introduction to Biostatistics Chapter 2: Getting Started With Python for Biostatistics Chapter 3: Exercise I - Cleaning and Describing Data Using Python Chapter 4: Part I Exemplar Project - Load, Clean, and Describe Diabetes Data in Python Part 2: Introduction to Python for Biostatistics - Methodology and Examples Chapter 5: Introduction to Python for Biostatistics Chapter 6: Biostatistical Inference Using Hypothesis Tests and Effect Sizes Chapter 7: Predictive Biostatistics Using Python Chapter 8: Part 2 Exercise - T-Test, ANOVA, and Linear and Logistic Regression Chapter 9: Biostatistical Inference and Predictive Analytics Using Cardiovascular Study Data Part 3: Clinical Study Design, Analysis, and Synthesizing Evidence Chapter 10: Clinical Study Design Chapter 11: Survival Analysis in Biomedical Research Chapter 12: Meta-Analysis—Synthesizing Evidence from Multiple Studies Chapter 13: Getting Started with Python for Biostatistics Chapter 14: Part 3 Exemplar Project - Meta-Analysis of Survival Data in Clinical Research Part 4: Biological and Statistical Variables and Frameworks, and a Final Practical Project from the Field of Biology Chapter 15: Understanding Biological Variables Chapter 16: Data Analysis Frameworks and Performance for Life Sciences Research Chapter 17: Part 4 Exercise - Performing Statistics for Biology Studies in Python This book leverages the author’s decade-long experience in biostatistics and data science to simplify the practical use of biostatistics with Python. The chapters show you how to clean and describe your data effectively, setting a solid foundation for accurate analysis and proficiency in biostatistical inference to help you draw meaningful conclusions from your data through hypothesis testing and effect size analysis. The book walks you through predictive modeling to harness the power of Python to create robust predictive analytics that can drive your research and professional projects forward. You'll explore clinical biostatistics, learn how to design studies, conduct survival analysis, and synthesize evidence from multiple studies with meta-analysis – skills that are crucial for making informed decisions based on comprehensive data reviews. The concluding chapters will enhance your ability to analyze biological variables, enabling you to perform detailed and accurate data analysis for biological research. This book's unique blend of biostatistics and Python helps you find practical solutions that make complex concepts easy to grasp and apply.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Coding with ChatGPT and Other LLMs Navigate LLMs for effective coding, debugging, and AI-driven development 🔘Edited by: Dr. Vincent Austin Hall 🔘Paperback : 304 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. What is ChatGPT and What are LLMs? 2. Unleashing the Power of LLMs for Coding: A Paradigm Shift 3. Code Refactoring, Debugging, and Optimization: A Practical Guide 4. Demystifying Generated Code for Readability 5. Addressing Bias and Ethical Concerns in LLM-Generated Code 6. Navigating the Legal Landscape of LLM-Generated Code 7. Security Considerations and Measures 8. Limitations of Coding with LLMs 9. Cultivating Collaboration in LLM-Enhanced Coding 10. Expanding the LLM Toolkit for Coders: Beyond LLMs 11. Helping Others and Maximizing Your Career with LLMs 12. The Future of LLMs in Software Development Keeping up with the AI revolution and its application in coding can be challenging, but with guidance from AI and ML expert Dr. Vincent Hall—who holds a PhD in machine learning and has extensive experience in licensed software development—this book helps both new and experienced coders to quickly adopt best practices and stay relevant in the field. You’ll learn how to use LLMs such as ChatGPT and Gemini to produce efficient, explainable, and shareable code and discover techniques to maximize the potential of LLMs. The book focuses on integrated development environments (IDEs) and provides tips to avoid pitfalls, such as bias and unexplainable code, to accelerate your coding speed. You’ll master advanced coding applications with LLMs, including refactoring, debugging, and optimization, while examining ethical considerations, biases, and legal implications. You’ll also use cutting-edge tools for code generation, architecting, description, and testing to avoid legal hassles while advancing your career.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 Software Architecture with Kotlin System calls, networking, efficiency, and security practices with practical projects in Golang 🔘Edited by: Alex Rios 🔘Paperback : 409 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. The essence of software architecture 2. Principles of software architecture 3. Polymorphism and alternatives 4. Peer-to-peer and client-server architecture 5. Model-view-controller (MVC) and Model-view-viewmodel (MVVM) 6. Micro-frontend, microservices, and serverless 7. Modular and layered architectures 8. Domain-driven development (DDD) and CQRS 9. Event-driven, event-sourced, and reactive systems 10. Idempotency, replication and recovery models in distributed systems 11. Auditing and monitoring models 12. Performance and scalability 13. Testing 14. Security 15. Beyond architecture Software Architecture with Kotlin is an insightful guide that explores various styles of software architecture with a focus on using the Kotlin programming language. This book delves into the principles, practices, and patterns that shape the architectural landscape of modern software systems. The book starts by establishing a strong foundation in software architecture, explaining key concepts such as architectural qualities and principles. You’ll learn how architectural decisions impact the quality of a system, such as scalability, reliability, and extendability. It address modern architecture topics like microservices, serverless, and event-driven architectures, providing insights into the challenges and trade-offs involved in adopting these architectural styles. You’ll discover practical tools that will help you make informed decisions and mitigate risks. All architectural patterns in this book are demonstrated using Kotlin. With its practical approach, real-world examples, and focus on Kotlin, this book will help you become a more proficient and impactful software architect.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l

📕 System Programming Essentials with Go System calls, networking, efficiency, and security practices with practical projects in Golang 🔘Edited by: Alex Rios 🔘Paperback : 409 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Packt 📝 Contents & Book Description:

1. Why Go? 2. Refreshing Concurrency and Parallelism 3. Understanding System Calls 4. File and Directory Operations 5. Working with System Events 6. Understanding Pipes in Inter-Process Communication 7. Hardware Automation 8. Memory Management 9. Analysing Performance 10. Networking 11. Telemetry 12. Distributing Your Apps 13. Capstone Project - Distributed Cache 14. Effective Coding Practices 15. Stay Sharp with System Programming Alex Rios, a seasoned Go developer and active community builder, shares his 15 years of expertise in designing large-scale systems through this book. It masterfully cuts through complexity, enabling you to build efficient and secure applications with Go's streamlined syntax and powerful concurrency features. In this book, you’ll learn how Go, unlike traditional system programming languages (C/C++), lets you focus on the problem by prioritizing readability and elevating developer experience with features like automatic garbage collection and built-in concurrency primitives, which remove the burden of low-level memory management and intricate synchronization.

🌐 Amazon 🌐 l @Skybook_it l 💬 l پشتیبانی l 🔰 l خرید از اسکای‌ بوک l