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The Art of Machine Learning

A comprehensive guide to building production-ready ML systems.

Pervez Hasan

Written by Pervez Hasan

Published 10/2025

Inside This Book

End-to-end project walkthroughs from scratch.

In-depth guides to model deployment (MLOps).

Modern techniques using PyTorch and Scikit-learn.

Clear, concise theory with practical examples.

Full source code available on GitHub.

Career advice and interview preparation tips.

Table of Contents

Chapter 1: The ML LandscapeFREE PREVIEW

What is Machine Learning?(10 pages)

The End-to-End ML Workflow(15 pages)

Setting Up Your Environment(8 pages)

Chapter 2: Data Preprocessing

Handling Missing Data(12 pages)

Encoding Categorical Data(14 pages)

Feature Scaling(10 pages)

Chapter 3: Mastering Linear Regression

Simple & Multiple Linear Regression(20 pages)

Project: Predicting House Prices(30 pages)

+ 9 more chapters including Deep Learning, NLP, and MLOps

What Readers Are Saying

"This is the book I wish I had when I started. It cuts through the noise and focuses on what's actually required on the job."

- Alex J., Senior ML Engineer

"The MLOps chapter alone is worth the price. Highly practical and well-explained."

- Sarah K., Data Scientist

Who This Book Is For

  • Aspiring Machine Learning Engineers and Data Scientists.
  • Software developers looking to transition into AI.
  • Students who want practical, hands-on project experience.
  • Professionals who need to understand how to deploy and manage ML models.

Description

This isn't just another theory book. "The Art of Machine Learning" is a hands-on, project-based guide to building, deploying, and managing real-world machine learning systems. We will move from foundational concepts to advanced production techniques.

You will learn the complete ML lifecycle, from data collection and preprocessing to model evaluation and deployment. Every chapter includes practical coding examples and a full end-to-end project, ensuring you build a strong portfolio as you learn.

Book Cover

$19.99(Ebook)

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This book includes:

  • 450 Pages
  • 12 In-depth Chapters
  • Full Source Code
  • Digital PDF, ePub & Kindle
  • Full lifetime access
  • Certificate of completion