Machine Learning Essentials You Always Wanted to Know

A Hands-On Beginner’s Guide to Mastering AI, Supervised, Unsupervised, and Deep Learning Algorithms. A Beginner’s Guide to Machine Learning with Hands-on Coding and Real-World ApplicationsCovers key algorithms and techniquesIdeal for students and professionalsHands-on implementation includedMaster the fundamentals of ML and take the first step towards a career in AI!In today’s rapidly evolving world, machine learning (ML) is no longer just for researchers or data scientists. From personalized recommendations on streaming platforms to fraud detection in banking, ML powers many aspects of our daily lives. As industries increasingly adopt AI-driven solutions, learning machine learning has become a valuable skill. Yet, many find the subject overwhelming, often intimidated by its mathematical complexity. That’s where Machine Learning Essentials You Always Wanted to Know (Machine Learning Essentials) comes in. This beginner-friendly guide offers a structured, step-by-step approach to understanding machine learning concepts without unnecessary jargon. Whether you are a student, a professional looking to transition into AI, or simply curious about how machines learn, this book provides a clear and practical roadmap to mastering ML.Authored by Dhairya Parikh, an experienced data engineer who returned to academia to refine his expertise, this book bridges the gap between theory and real-world application. It simplifies the core concepts of ML, breaking them down into digestible explanations paired with hands-on coding exercises to help you apply what you learn.What You’ll Learn:The fundamentals of machine learning and how it powers modern technologyThe three key types of ML-Supervised, Unsupervised, and Reinforcement LearningHow to combine algorithms, data, and models to develop AI-driven solutionsPractical coding techniques to build and implement machine learning modelsPart of Vibrant Publishers’ Self-Learning Management Series, this book serves as a valuable guide for building machine learning skills, enhancing your expertise, and advancing your career in AI and data science.