Books

Build a complete LLM inference engine in C++ — from a blank project to a working Transformer that loads a real model and generates text. Forged one challenge at a time, with tests that prove every piece works before you move on.

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.

Build a strong foundation in data structures and algorithms with clear explanations and practical Python examples. From core concepts to advanced techniques, this guide helps you understand how efficient software is designed so you can write better code with confidence and solve real programming challenges.

 Why Should You Study This Book?Comprehensive Coverage: This book covers all essential C programming concepts, from the basics to intermediate topics, making it suitable for students across various academic levels, including Class 12, graduates, and MCA students.Clear Explanations: The concepts are presented in a simple, easy-to-understand manner. Whether you are a novice or have some programming experience, you’ll find the explanations clear and easy to follow.Practical Focus: It includes numerous hands-on examples and practice problems to reinforce the concepts. With each chapter, you will have the opportunity to write real C programs, which will help you solidify your understanding and develop practical programming skills.Real-World Applications: The book does not just cover theory. It guides you through creating practical programs such as a basic calculator, a library management system, and even a text editor. These projects provide a real-world context to what you’re learning, making it easier to grasp how C programming is used in various applications.Skill Development: Learning C programming will sharpen your problem-solving abilities, logical thinking, and analytical skills. These skills are essential not only for programming but also for tackling complex challenges in various fields of study and work.Error Handling and Debugging: The book emphasizes the importance of writing error-free and optimized code. It introduces common pitfalls and debugging techniques, helping students become efficient and error-resistant programmers.Preparation for Further Studies: If you're planning to learn advanced topics like data structures, algorithms, or even system programming, this book provides the foundation you'll need. Mastering C will give you a strong base for learning other programming languages and advanced computing concepts.

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.

Learn the basics of programming with runnable flowcharts!Develop a groundwork for your next programming language, be that Python, Java, C# or any other.Try interactive examples in a matter of seconds!

What if your software could compute on sensitive data without ever seeing it? Private Computing with Homomorphic Encryption takes you from the core ideas to working, production-minded systems. Learn the math, schemes, libraries and design patterns you need to build with HE, judge its tradeoffs and know when it is the right tool for the job.

Big O is not about seconds. It is about what happens to your work when your input gets ten times bigger, and that is the question interviewers are really asking. This book builds the notation from a list of names you can watch being searched, then hands you twenty everyday jobs in ten pairs and asks you to name the shape of each one.

Every news feed is full of AI buzzwords: Transformers, tokens, embeddings, context windows, hallucinations, objective functions. Yet most explanations are either dense academic textbooks or empty marketing fluff. ☕ Coffee Break AI is your practical guide to AI. Written in plain English with warm real-world analogies. It breaks down the core mechanisms of AI into 40 bite-sized chapters.

We'll be writing kernels in Rust and seeing how they match up with their C++ equivalents. If you feed a GPU properly, you'll see bandwidth quadruple from just one changed subscript. It'll get you working with thousands of threads, pricing a financial option based on an exact formula, and shipping an inference pipeline that outruns its Python equivalent for reasons you can name.

JavaScript ve Node.js öğrenmek isteyenler için başlangıçtan profesyonel seviyeye uzanan kapsamlı bir rehber. 1300+ sayfalık bu eser; modern JavaScript, Node.js, REST API, OOP, asenkron programlama, veritabanları, Clean Code, SOLID prensipleri, yazılım mimarisi ve gerçek dünya projeleriyle yalnızca kod yazmayı değil, yazılım mühendisi gibi düşünmeyi öğretir.

The future of technology is decentralized—and blockchain is at the center of this transformation.From global banks and fintech companies to healthcare organizations, supply chain enterprises, gaming platforms, governments, and Web3 startups, blockchain technology is creating entirely new career opportunities. Companies around the world are actively searching

Learn how to build a modern programming language from scratch in Rust. By implementing a complete language called Rune, you will explore every stage of language design, from lexing and parsing to type checking, virtual machines, LLVM code generation, and developer tooling, with practical code and clear explanations throughout.

Make your Python AI code up to 100× faster using NumPy vectorization, Numba, parallel execution, and GPU acceleration. Learn through practical benchmarks and real-world optimization examples.