Skybook_IT (Overview)

📕 CompTIA Tech+ Study Guide Exam FC0-U71 🔘Edited by: Quentin Docter 🔘Paperback : 771 pages (B5) 🔘Edition : 3 🔘Year : 2024 🔘Publisher : Sybex (Wiley) • Optimized learning resources to get you up to speed as fast as possible • Exam resources designed to reduce test anxiety and familiarize you with testing procedure and content • One full year of access to the Sybex online learning environment, complete with real-world examples and scenarios, objective maps, and a glossary of useful terminology

📕 Optimization Algorithms AI techniques for design, planning, and control problems 🔘Edited by: Alaa Khamis 🔘Paperback : 669 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Manning • The core concepts of search and optimization • Deterministic and stochastic optimization techniques • Graph search algorithms • Trajectory-based optimization algorithms • Evolutionary computing algorithms • Swarm intelligence algorithms • Machine learning methods for search and optimization problems • Efficient trade-offs between search space exploration and exploitation • State-of-the-art Python libraries for search and optimization

📕 React in Depth 🔘Edited by: Morten Barklund 🔘Paperback : 434 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Manning • Assess technologies in the React ecosystem • Implement advanced component patterns to improve React code • Optimize React performance for a smooth user experience • Use developer tooling for better code maintenance and debugging • Work with TypeScript for type safety • Use CSS in JavaScript for efficient styling • Manage data in React, including remote data and reactive caching • Unit test React components for quality assurance and bug prevention • Use popular React frameworks for building production-ready applications

📕 Build a Large Language Model (From Scratch) 🔘Edited by: Sebastian Raschka 🔘Paperback : 370 pages (B5) 🔘Edition : 1 🔘Year : 2025 🔘Publisher : Manning • Plan and code all the parts of an LLM • Prepare a dataset suitable for LLM training • Fine-tune LLMs for text classification and with your own data • Use human feedback to ensure your LLM follows instructions • Load pretrained weights into an LLM

📕 Dead Simple Python Idiomatic Python for the Impatient Programmer 🔘Edited by: Jason C. McDonald 🔘Paperback : 755 pages (B5) 🔘Edition : 1 🔘Year : 2023 🔘Publisher : No Starch Press • Make Python's dynamic typing work for you to produce cleaner, more adaptive code. • Harness advanced iteration techniques to structure and process your data. • Design classes and functions that work without unwanted surprises or arbitrary constraints. • Use multiple inheritance and introspection to write classes that work intuitively. • Improve your code's responsiveness and performance with asynchrony, concurrency, and parallelism. • Structure your Python project for production-grade testing and distribution

📕 CompTIA Linux+ XK0-005 Cert Guide Advance your IT career with hands-on learning 🔘Edited by: Ross Brunson 🔘Paperback : 906 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Pearson • Complete coverage of the exam objectives and a test-preparation routine designed to help you pass the exams • Do I Know This Already? quizzes, which allow you to decide how much time you need to spend on each section • Chapter-ending Key Topic tables, which help you drill on key concepts you must know thoroughly • The powerful Pearson Test Prep Practice Test software, complete with hundreds of well-reviewed, exam-realistic questions, customization options, and detailed performance reports • An online, interactive Flash Cards application to help you drill on Key Terms by chapter • A final preparation chapter, which guides you through tools and resources to help you craft your review and test-taking strategies • Study plan suggestions and templates to help you organize and optimize your study time

📕 The Complete Obsolete Guide to Generative AI 🔘Edited by: David Clinton 🔘Paperback : 240 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Manning • Just enough background info on AI! What an AI model is how it works • Ways to create text, code, and images for your organization's needs • Training AI models on your local data stores or on the internet • Business intelligence and analytics uses for AI • Building your own custom AI models • Looking ahead to the future of generative AI

📕 CSS in Depth 🔘Edited by: Keith J. Grant 🔘Paperback : 545 pages (B5) 🔘Edition : 2 🔘Year : 2024 🔘Publisher : Manning • Create a web page with layout methods • Develop essential website components, like dropdown menus and dialog boxes • Make your website fully responsive across devices • Organize your CSS for easy future maintenance • Implement designer mockups with attention to detail • Use animations to guide user focus • Avoid common CSS pitfalls

📕 Mastering PowerShell Scripting Automate repetitive tasks and simplify complex administrative tasks using PowerShell 🔘Edited by: Chris Dent 🔘Paperback : 827 pages (B5) 🔘Edition : 5 🔘Year : 2024 🔘Publisher : Packt • Create scripts that can be run on different systems • PowerShell is highly extensible and can integrate with other programming languages • Discover the powerful command-line interface that enables users to perform various operations with ease • Create reusable scripts and functions in PowerShell • Utilize PowerShell for various purposes, including system administration, automation, and data processing • Integrate PowerShell with other technologies such as .NET, COM, and WMI • Work with common data formats such as XML, JSON, and CSV in PowerShell • Create custom PowerShell modules and cmdlets to extend its functionality

📕 AI-Powered Developer Build great software with ChatGPT and Copilot 🔘Edited by: Nathan B. Crocker 🔘Paperback : 242 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Manning • Harness AI to help you design and plan software • Use AI for code generation, debugging, and documentation • Improve your code quality assessments with the help of AI • Articulate complex problems to prompt an AI solution • Develop a continuous learning mindset that keeps you up to date • Adapt your development skills to almost any language

📕 Data Storytelling with Altair and AI 🔘Edited by: Angelica Lo Duca 🔘Paperback : 386 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Manning • Using Python Altair for data visualization • Using Generative AI tools for data storytelling • The main concepts of data storytelling • Building data stories with the DIKW pyramid approach • Transforming raw data into a data story

📕 Idiomatic Rust Code like a Rustacean 🔘Edited by: Brenden Matthews 🔘Paperback : 257 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Manning • Fluent interfaces for creating delightful APIs • The Builder pattern to encapsulate data and perform initialization • Immutable data structures that help you avoid hard-to-debug data race conditions • Functional programming patterns • Anti-patterns and what not to do in Rust

📕 Large Language Models A Deep Dive: Bridging Theory and Practice 🔘Edited by: Uday Kamath, Kevin Keenan, Garrett Somers, Sarah Sorenson 🔘Paperback : 508 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Springer • Over 100 techniques and state-of-the-art methods, including pre-training, prompt-based tuning, instruction tuning, parameter-efficient and compute-efficient fine-tuning, end-user prompt engineering, and building and optimizing Retrieval-Augmented Generation systems, along with strategies for aligning LLMs with human values using reinforcement learning • Over 200 datasets compiled in one place, covering everything from pre- training to multimodal tuning, providing a robust foundation for diverse LLM applications • Over 50 strategies to address key ethical issues such as hallucination, toxicity, bias, fairness, and privacy. Gain comprehensive methods for measuring, evaluating, and mitigating these challenges to ensure responsible LLM deployment • Over 200 benchmarks covering LLM performance across various tasks, ethical considerations, multimodal applications, and more than 50 evaluation metrics for the LLM lifecycle • Nine detailed tutorials that guide readers through pre-training, fine- tuning, alignment tuning, bias mitigation, multimodal training, and deploying large language models using tools and libraries compatible with Google Colab, ensuring practical application of theoretical concepts • Over 100 practical tips for data scientists and practitioners, offering implementation details, tricks, and tools to successfully navigate the LLM life- cycle and accomplish tasks efficiently

📕 Getting Started with Docker 🔘Edited by: Nigel Poulton 🔘Paperback : 101 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Nielsen Book • Install Docker • Run your first container • Containerize a sample app • Work with Docker Hub • Deploy and manage a multi-container app with Docker Compose • Deploy a WebAssembly app with Docker

📕 Programming with Python for Engineers 🔘Edited by: Sinan Kalkan, Onur T. Şehitoğlu, Göktürk Üçoluk 🔘Paperback : 306 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Springer • The book contains interactive content for illustration of important concepts, where the user can provide input and by clicking buttons, trace through the steps. • Each chapter is also accessible as a Jupyter Notebook page and every code piece is executable. This allows the readers to run code examples in chapters immediately, to make changes and gain a better grasp of the concepts presented. • The coverage of topics is complemented by illustrative examples and exercises.

📕 Master Vue.js in 6 Days Become a Vue.js Expert in Under a Week 🔘Edited by: Eric Sarrion 🔘Paperback : 374 pages (B5) 🔘Edition : 1 🔘Year : 2024 🔘Publisher : Apress • Understand key Vue.js principles and concepts. • Create Reactive user interfaces. • Acquire a comprehensive understanding of the Vue.js framework.

📕 OCP Oracle Certified Professional Java SE 17 Developer (Exam 1Z0-829) Programmer’s Guide 🔘Edited by: Khalid A. Mughal, Vasily A. Strelnikov 🔘Paperback : 1853 pages (B5) 🔘Edition : 3 🔘Year : 2023 🔘Publisher : Oracle Press • Easy to find coverage of key topics relevant to each exam objective • An introduction to essential concepts in object-oriented programming (OOP) and functional-style programming • In-depth coverage of declarations, access control, operators, flow control, OOP techniques, lambda expressions, streams, modules, concurrency, Java I/O, key API classes, and much more • Program output demonstrating expected results from complete Java programs • Unique diagrams to illustrate important concepts, such as Java I/O, modules, and streams • Extensive use of (Unified Modeling Language) UML to illustrate program design • Dozens of review questions with annotated answers to help prepare for the exam and a complete mock exam

📕 Core Java for the Impatient 🔘Edited by: Cay S. Horstmann 🔘Paperback : 577 pages (B5) 🔘Edition : 3 🔘Year : 2023 🔘Publisher : Addison-Wesley • Test code as you create it with JShell • Improve your object-oriented design with records and sealed classes • Effectively use text blocks, switch expressions, and pattern matching • Understand functional programming with lambda expressions • Streamline and optimize data management with the Streams API • Use modern library features and threadsafe data structures to implement concurrency reliably • Work with the modularized Java API and third-party modules • Take advantage of API improvements for working with collections, input/output, regular expressions, and processes • Learn the APIs for date/time processing and internationalization

📕 Pandas for Everyone Python Data Analysis 🔘Edited by: Daniel Y. Chen 🔘Paperback : 512 pages (B5) 🔘Edition : 2 🔘Year : 2024 🔘Publisher : Addison-Wesley • Work with DataFrames and Series, and import or export data • Create plots with matplotlib, seaborn, and pandas • Combine data sets and handle missing data • Reshape, tidy, and clean data sets so they’re easier to work with • Convert data types and manipulate text strings • Apply functions to scale data manipulations • Aggregate, transform, and filter large data sets with groupby • Leverage Pandas’ advanced date and time capabilities • Fit linear models using statsmodels and scikit-learn libraries • Use generalized linear modeling to fit models with different response variables • Compare multiple models to select the “best” one • Regularize to overcome overfitting and improve performance • Use clustering in unsupervised machine learning

📕 Quick Start Guide to Large Language Models Strategies and Best Practices for Using ChatGPT and Other LLMs 🔘Edited by: Sinan Ozdemir 🔘Paperback : 281 pages (B5) 🔘Edition : 1 🔘Year : 2023 🔘Publisher : Addison-Wesley The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems.