Hands-On Machine Learning with PyTorch, TensorFlow, and Scikit-Learn: Step-by-Step Projects for Beginners and Beyond

Name: Hands-On Machine Learning with PyTorch, TensorFlow, and Scikit-Learn: Step-by-Step Projects for Beginners and Beyond
Brand: Independently Published
SKU: 9798268323191
Price: 2712.0 INR
Availability: InStock

by Adrian Devlin

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ISBN13: 9798268323191
Binding: Paperback
Subject: N/A
Publisher: Independently Published
Publisher Imprint: Independently Published
Publication Date: October 3, 2025
Pages: 308
Original Price: GBP 23.78
Language: English
Edition: N/A
Item Weight: 536 grams
BISAC Subject(s): Machine Theory

About The Book

Does machine learning feel out of reach-something only experts or PhDs can understand?
If you've ever felt intimidated by complex jargon or worried you don't "belong" in tech, this book is here to change that. Hands-On Machine Learning with PyTorch, TensorFlow, and Scikit-Learn: Step-by-Step Projects for Beginners and Beyond is your friendly, confidence-building guide to learning AI and machine learning-no prior coding or math experience required.

Inside, you'll discover a warm, supportive approach that makes technical concepts simple, practical, and even enjoyable. Instead of overwhelming theory, you'll gain real skills by building actual projects using today's most popular frameworks: PyTorch, TensorFlow, and Scikit-Learn. Each chapter walks you through every step at a beginner's pace, with clear explanations and hands-on coding exercises you can follow along with at home.

What you'll learn inside this book:

How to set up your Python environment and start coding with ease.
Beginner-friendly introductions to classification, regression, clustering, and deep learning.
Practical projects with real-world datasets-such as image recognition and text classification-using PyTorch, TensorFlow, and Scikit-Learn side by side.
Confidence-building strategies that normalize mistakes, encourage curiosity, and celebrate small wins.
How to improve, evaluate, and even deploy your models using modern tools.
A gentle introduction to responsible AI, bias, and the future of machine learning.

Unlike dense textbooks or one-size-fits-all tutorials, this book was designed with complete beginners in mind. You'll always know why you're doing something, not just what to type. Each chapter feels like having a patient mentor at your side-someone who explains complex ideas in plain English, helps you troubleshoot when things go wrong, and cheers you on as you grow.

By the time you finish, you won't just understand machine learning-you'll have built real projects, gained practical skills, and discovered that AI is not only approachable but also exciting and rewarding.

If you've ever dreamed of learning AI but didn't know where to start, this is your step-by-step guide.
Take the leap today, and let this book be your supportive companion on a journey that turns curiosity into confidence and beginners into creators.

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