Overview

Artificial Intelligence is no longer the future-it is the present. From smartphones and recommendation systems to self-driving cars, intelligent chatbots, and Large Language Models, Machine Learning and AI are transforming how the world works. Machine Learning, Deep Learning & Artificial Intelligence is a complete, structured, and practical guide designed to take you from absolute fundamentals to advanced modern AI systems, including Transformers, Large Language Models (LLMs), Prompt Engineering, Responsible AI, and the future of AI. This book is written with a clear learning philosophy: Understand concepts deeply Apply them practically Think ethically and responsibly Unlike books that focus only on theory or only on coding, this book provides a balanced, step-by-step learning pathcombining: Clear explanations with real-world intuition Essential mathematics explained simply Python-based machine learning workflows Classical ML algorithms (Regression, KNN, Trees, SVM, Naive Bayes) Unsupervised learning and clustering techniques Deep Learning fundamentals and neural networks CNNs, RNNs, LSTMs, GRUs, and Transfer Learning Attention mechanism and Transformers Large Language Models (LLMs) and Prompt Engineering Real-world AI applications and industry case studies AI ethics, bias, safety, and Responsible AI Future trends, careers, and AI's long-term impact Each chapter is carefully designed to include: Concept explanations Practical understanding Exercises and hands-on tasks Interview and exam-oriented questions This makes the book ideal for: Students preparing for exams, projects, and interviews Working professionals transitioning into Data Science, ML, or AI roles Engineers and developers looking to upgrade skills Educators and trainers seeking a structured reference Self-learners who want a single, comprehensive AI book Special attention is given to modern AI topics such as: Large Language Models (LLMs) Prompt Engineering techniques Real-world deployment challenges Ethical risks, bias, and AI governance By the end of this book, you will not only understand how AI models work, but also when, why, and how to use them responsibly in real-world scenarios. Whether your goal is to learn Machine Learning from scratch, crack AI interviews, build intelligent systems, or understand the future of AI, this book serves as a complete roadmap from beginner to advanced level. This is not just a technical book-it is a guide to thinking intelligently and responsibly in the age of Artificial Intelligence.

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