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Data to Decision: A journey of Machine Learning
In today’s world, Machine Learning is no longer confined to research labs or big tech companies — it powers everything from recommendation systems to fraud detection and healthcare predictions. Yet, many learners struggle to bridge the gap between theory and practical application.
This book has been written with a simple to make Machine Learning accessible, practical, and learner-friendly. Unlike traditional resources that either overwhelm with mathematics or oversimplify concepts, this book strikes a balance
Starting from the basics — ensuring even beginners can follow along.Focusing on data — since working with data is at the heart of every ML project.Hands-on examples and step-by-step explanations — to help readers implement what they learn.Bridging theory with practice — explaining the "why" behind algorithms, and also the "how" with real-world datasets.Progressive learning path — from understanding data, preprocessing, model building, evaluation, to advanced topics.Whether you are a student, a researcher, or a practitioner stepping into the world of ML, this book will serve as a companion guide to help you not just learn, but apply Machine Learning effectively.
This book has been written with a simple to make Machine Learning accessible, practical, and learner-friendly. Unlike traditional resources that either overwhelm with mathematics or oversimplify concepts, this book strikes a balance
Starting from the basics — ensuring even beginners can follow along.Focusing on data — since working with data is at the heart of every ML project.Hands-on examples and step-by-step explanations — to help readers implement what they learn.Bridging theory with practice — explaining the "why" behind algorithms, and also the "how" with real-world datasets.Progressive learning path — from understanding data, preprocessing, model building, evaluation, to advanced topics.Whether you are a student, a researcher, or a practitioner stepping into the world of ML, this book will serve as a companion guide to help you not just learn, but apply Machine Learning effectively.
98 pages, Kindle Edition
Published August 28, 2025
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