Algorithm

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.

The Python interview guide written from the interviewer's side of the table. 35 chapters. Every benchmark measured. Every line of code verified. What senior engineers actually get asked — and what separates the ones who get the offer.

Mastering Algorithms: From Fundamentals to Advanced Applications for Students and Professionals provides a structured journey through algorithm fundamentals, complexity analysis, design strategies, optimization techniques, and advanced graph algorithms.Explore Divide and Conquer, Greedy Algorithms, Dynamic Programming, Backtracking, Branch and Bound, graph traversal, shortest paths.

Mastering Data Structures Using C – QUESTION BANK: 1000+ Conceptual Questions for Students and Professionals is a comprehensive practice resource featuring MCQs, short-answer questions, detailed mid-length questions with answers, and solved programming questions.Covering arrays, linked lists, stacks, queues, trees, graphs, searching, sorting, hashing, file organization, recursion, backtracking.

Data Structures in C: A Comprehensive Guide for Students transforms complex data-structure concepts into clear explanations, step-by-step algorithms, practical C programs, detailed code walkthroughs, real-world applications, and hands-on exercises.From arrays, linked lists, stacks, and queues to trees, graphs, searching, sorting, recursion

Artificial intelligence is reshaping financial markets. Intelligent Markets shows you how to build production-ready AI trading systems from first principles, combining market fundamentals, practical architecture, and fully runnable code to create autonomous agents that can research, execute, and manage trades in live markets.

Programming Ideas closes the gap between introductory programming books and computer science textbooks. It teaches you how to write programs that solve a wide range of practical problems, from drawing fractals to compressing files and computing Pi, and it carefully explains both the required programming techniques and the resulting programs.

Learn how to create profitable Facebook Ads and Google Ads that generate more traffic, leads, and sales. This practical step-by-step guide teaches you how to target the right audience, optimize your campaigns, reduce wasted ad spend, and maximize your return on investment.

After 1,000+ interviews, I kept seeing the same gaps: engineers who use shared_ptr daily but can't explain the control block; developers who write multithreaded code without understanding the memory model they're relying on. This book is the resource I wished existed. Free preview includes Chapter 3: OOP & Polymorphism — the chapter that eliminates more candidates than any other.

Master Discrete Mathematics — the foundation of Computer Science. Comprehensive guide specially designed for BCA & MCA students with detailed explanations, solved examples, real-world applications, and exam-focused practice. Perfect for university exams, GATE, and interviews.

How does code actually run under the hood? Stop guessing and master the hidden physics of execution. Learn how Python and Java truly manage memory, layout data structures, and drive high-performance algorithms.

Artificial Intelligence doesn't become intelligent by chance—it learns through optimization.Every neural network improves because of Gradient Descent.Every recommendation system depends on matrix factorization.Every deep learning model relies on numerical computation.Numerical Methods with Artificial Intelligence Applications – Volume 2 takes you beyond the fundamentals and into the advanced mathematical engines driving modern AI.Discover how optimization algorithms like Adam, RMSProp, Newton's Method, and Conjugate Gradient train intelligent systems. Explore numerical linear algebra, probabilistic AI, evolutionary computation, Python implementations, and real-world AI case studies that reveal the mathematics behind today's most powerful technologies.Whether you're building machine learning models, conducting AI research, or strengthening your computational skills, this volume equips you with the advanced numerical techniques essential for the next generation of intelligent systems.Master the algorithms that teach machines how to learn.

Artificial Intelligence is built on mathematics—and numerical methods are at its core.What happens behind gradient descent? How do optimization algorithms converge? Why are interpolation, differentiation, and integration essential for machine learning?Discover the mathematical engine that powers modern AI.Numerical Methods with Artificial Intelligence Applications (Volume 1) transforms traditional numerical methods into practical AI tools through real-world examples, optimization techniques, and machine learning applications.Whether you're a student, researcher, educator, or AI enthusiast, this book will help you understand the algorithms that make intelligent systems possible.