Books

I wrote this book to show exactly what happens when you add Rust to the kernel. Not as a toy. Not as a single driver in a conference demo. It's a full module that covers process management, memory allocation, file systems, networking, device drivers, inter-process communication, and even machine learning inference. It's all built on safe abstractions, all compiled into one loadable binary, all tested on a running kernel. You'll find that each chapter adds new source files to the same module.

A concise, illustrated guide to algorithms and data structures, perfect for coding interviews, classes, or self-study. Covers key concepts, from fundamentals to graphs, trees, sorting, and search techniques.

1000 carefully designed C++ problems across 8 progressive volumes — from your very first line of code to advanced algorithms. Every single solution is compiled and tested on g++, with hints, complexity analysis, and a clear explanation for each. A complete, structured path from beginner to mastery.

An introduction to actor-critic algorithms as dynamical systems: featuring hand-computable examples, fast-slow reductions, and machine-checked Lean 4 proofs

A book designed to help you transition from merely knowing Python to cracking Leetcode patterns. This book explains core DSA concepts through clear, intuitive analogies and walks you through the most important Leetcode patterns. If you're aiming to ace your next coding interview, this is the book I wish I had when I started.

Principios fundamentales para entender cómo organizar y manipular datos de manera eficiente. Con un enfoque didáctico y accesible.

Why learn one programming language when you can understand three at once? This book introduces the foundations of programming through a powerful side-by-side comparison of Python, Java, and C#, enabling readers to build strong conceptual understanding, transferable coding skills, and a solid pathway toward modern software engineering.

By diving into this book, students will:1.     Master Supervised Learning Fundamentals Gain strong conceptual understanding and practical competence.2.     Evate & Deploy Models Effectively Understand how to build, validate, interpret, and deploy high-quality models.3.     Think Critically about AI Systems Develop ethical awareness and critical reasoning regarding data bias and model behavior.

·        Comprehensive Learning Path: The book starts with basics and gradually leads you to advanced topics, making it accessible for beginners and challenging for advanced learners.·        Contextual AI Applications: Every concept is illustrated with AI and ML examples, ensuring relevance and immediate applicability.·        Enhanced Understanding of AI Models: Knowing data structures like trees and graphs clarifies how decision trees or knowledge graphs operate internally, boosting your model-building skills.·        Algorithm Efficiency Awareness: Understanding algorithm complexity and heuristics allows you to write optimized AI programs that can handle large datasets and real-time processing.·        Practical Coding Exercises: With implementations in Python, you will develop a coding mindset essential for AI practitioners.·        Preparation for Research and Development: The book equips you to contribute to AI research and innovate new algorithms or improve existing ones.

A practical interview reference covering Modern C++ language features, STL usage, concurrency, and performance (525 manuscript pages).

Master the future of technology with this definitive guide to Modern Data Science. Unlock actionable insights through Analytics, Machine Learning, and Big Data strategies. Perfect for beginners and pros wanting a logic-first approach to data-driven decision making.

Stop being a syntax typist. Master Clean Code Architecture and Algorithmic Thinking to become a professional Software Architect in 2026. This blueprint teaches you to build Scalable Systems using Binary Logic, Big O Notation, and proven Software Engineering Patterns. Perfect for the modern Backend Developer, self-taught coder, and Tech Entrepreneur looking to design high-performance software from scratch.

Learn Python step by step with a practical workbook designed for absolute beginners. This book combines clear explanations, visual flowcharts, exercises, and hands-on coding projects to help you understand programming from the ground up.

This book introduces students to the fundamentals of Python programming through a structured and practical learning approach. Designed for beginners, the book focuses on problem solving, algorithms, and core programming concepts using clear explanations and hands-on exercises. Readers will learn how to build Python programs step by step while developing computational thinking skills.

Crack mobile coding interviews by mastering patterns instead of memorization. This book teaches you how to quickly recognize interview problems and solve them confidently using reusable Swift and Kotlin templates, exactly the way top iOS and Android candidates do. If you want to think clearly, code fast, and explain your solutions under pressure—this book is for you.