Books

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 is an extensive collection of fun and fascinating programming projects for intermediate to advanced programmers. It closes the gap between introductory programming books and computer science textbooks by showing you how to solve a wide range of practical problems, from drawing fractals to compressing files and computing Pi, and carefully explains both the required algorithms and techniques as well as 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.

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.

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.

A practical, code-first guide to physics-informed machine learning for scientists and engineers. You'll build a working Physics-Informed Neural Network from scratch in PyTorch, solve a real differential equation, and verify it against the exact solution — staying honest about both the power and the limits of the method.

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

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.

A practical and pedagogical introduction to the Discrete Fourier Transform (DFT), combining theory, numerical examples, and MATLAB/Python implementations for students, engineers, and educators.

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.