Machine Learning Essentials You Always Wanted to Know: A Hands-On Beginner's Guide to Mastering AI, Supervised, Unsupervised, and Deep Learning Algorithms
Machine learning is everywhere. It filters your inbox, shapes your streaming queue, and quietly underpins decisions in banking, healthcare, and beyond. Yet for most beginners, picking up a textbook on the subject feels a bit like being handed a map written in a foreign language. Author Dhairya Parikh, a data engineer who returned to academia to sharpen his own skills, sets out to change that with this approachable introductory guide. His dual perspective, practical professional and returning student, gives the writing a grounded quality that purely academic texts often lack. The book walks readers through the three principal categories of machine learning (supervised, unsupervised, and reinforcement learning), building understanding gradually rather than front-loading readers with intimidating theory. Mathematical concepts are introduced only where genuinely necessary, and each is paired with hands-on coding exercises that let you test ideas as you go. It's the kind of structure that suits students preparing for careers in AI as much as working professionals looking to pivot. The explanations are clear without being dumbed down, which is a harder balance to strike than it sounds. Parikh avoids the trap of treating beginners as fragile, instead trusting them to absorb real concepts when presented logically. Part of Vibrant Publishers' Self-Learning Management Series, the book also covers how algorithms, data, and models can be combined to produce practical, AI-driven solutions. A solid, well-organised starting point for anyone curious about how machines actually learn.
- Author: Dhairya Parikh
- Publisher: Vibrant Publishers
- Genre: Industry-Specific Business
- ISBN: 978-1636513775
- Pages: 276 pages