A Hacker's Guide to Machine Learning

Welcome to "A Hacker's Guide to Machine Learning" (HGML). This book is designed to empower you with the knowledge, skills, and confidence to apply machine learning techniques to real-world problems. This guide lightly touches on theoretical aspects of machine learning, while it focuses on practical applications and provides a hands-on approach that you can use across a variety of domains.

If you're a developer, engineer, data scientist, or even a curious enthusiast looking to dive into machine learning, you'll find this book a valuable resource. We assume that you have a basic understanding of programming and mathematics, but even if you're new to these fields, we've tried to make the content approachable. The code snippets are presented in Python using open source models and tools.

Table of Contents:

• Chapter 1: Introduction
• Chapter 2: Natural Language Parsing (NLP)
• Chapter 3: Recommender Systems
• Chapter 4: Computer Vision
• Chapter 5: Supervised Learning
• Chapter 6: Unsupervised Learning
• Chapter 7: Intelligent Agents

FAQ

Is this book beginner friendly?

Absolutely! "A Hacker's Guide to Machine Learning" is designed to be accessible for beginners, offering a step-by-step journey through the fundamentals of machine learning, without assuming prior expertise in the field.

What's the refund policy?

If you're not satisfied with your purchase, we offer a full refund within 30 days, no questions asked.