---
product_id: 806734120
title: "Machine Learning: Algorithms, Theory and Practice — A Comprehensive Hands-On Guide with Python"
price: "C$4891"
currency: NIO
in_stock: false
reviews_count: 8
url: https://www.desertcart.ni/products/806734120-machine-learning-algorithms-theory-and-practice-a-comprehensive-hands-on
store_origin: NI
region: Nicaragua
---

# Machine Learning: Algorithms, Theory and Practice — A Comprehensive Hands-On Guide with Python

**Price:** C$4891
**Availability:** ❌ Out of Stock

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- **What is this?** Machine Learning: Algorithms, Theory and Practice — A Comprehensive Hands-On Guide with Python
- **How much does it cost?** C$4891 with free shipping
- **Is it available?** Currently out of stock
- **Where can I buy it?** [www.desertcart.ni](https://www.desertcart.ni/products/806734120-machine-learning-algorithms-theory-and-practice-a-comprehensive-hands-on)

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## Description

Review: For Any Aspiring Machine Learning Practitioner - This book strikes the perfect balance between theory and hands-on practice. As someone looking to deepen my understanding of machine learning, I found the progression from core concepts and Python basics to advanced topics like transformers and generative AI both logical and engaging. The real-world coding tutorials and use of key libraries make it easy to follow along and apply what you learn. The glossary and sections are also great additions for quick reference. Whether you're a student or transitioning into an role, this guide is an excellent resource.
Review: Understand Machine Learning with clarity and depth - This book offers an exceptional combination of clarity and depth. Its structured approach covers topics from the basics to transformers, providing insights for newcomers and experienced readers seeking a quick review. With step-by-step Python notebooks, regular checkpoints, and a glossary of 300 terms, the learning curve is made accessible rather than daunting. I particularly appreciated the balanced explanations of "why-then-how" that introduce each code block. Certain chapters, like those on reinforcement learning and diffusion models, touch on advanced mathematics that power users will eventually require. Most datasets are small, leaving production-scale considerations for the reader to explore. This book is a clear, useful resource that deserves a place on your desk, ideally complemented by more in-depth, domain-specific texts as you progress beyond the tutorials.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #636,410 in Kindle Store ( See Top 100 in Kindle Store ) #142 in Information Technology #5,117 in Computers & Technology (Books) |

## Images

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## Customer Reviews

### ⭐⭐⭐⭐⭐ For Any Aspiring Machine Learning Practitioner
*by R***R on May 26, 2025*

This book strikes the perfect balance between theory and hands-on practice. As someone looking to deepen my understanding of machine learning, I found the progression from core concepts and Python basics to advanced topics like transformers and generative AI both logical and engaging. The real-world coding tutorials and use of key libraries make it easy to follow along and apply what you learn. The glossary and sections are also great additions for quick reference. Whether you're a student or transitioning into an role, this guide is an excellent resource.

### ⭐⭐⭐⭐⭐ Understand Machine Learning with clarity and depth
*by R***O on May 9, 2025*

This book offers an exceptional combination of clarity and depth. Its structured approach covers topics from the basics to transformers, providing insights for newcomers and experienced readers seeking a quick review. With step-by-step Python notebooks, regular checkpoints, and a glossary of 300 terms, the learning curve is made accessible rather than daunting. I particularly appreciated the balanced explanations of "why-then-how" that introduce each code block. Certain chapters, like those on reinforcement learning and diffusion models, touch on advanced mathematics that power users will eventually require. Most datasets are small, leaving production-scale considerations for the reader to explore. This book is a clear, useful resource that deserves a place on your desk, ideally complemented by more in-depth, domain-specific texts as you progress beyond the tutorials.

### ⭐⭐⭐⭐ From zero to ML hero—with code that actually makes sense
*by J***K on April 20, 2025*

Machine Learning: Algorithms, Theory and Practice is the kind of resource you wish you had from day one. It’s not just another theory-heavy textbook or copy-paste tutorial book—it bridges the two beautifully. Whether you’re a student, a self-taught dev, or someone finally ready to dip a toe into the deep AI pool, this guide walks you through the how and the why. Bonus: it actually explains things in plain English before throwing code at you. What sets it apart is the progression—it builds your understanding step by step, from basic regression to transformer models and diffusion-based generative AI (yes, the stuff powering all the cool art generators). You’ll come away not just knowing how to run ML code in Python, but why it works. With over 300 glossary terms, real-world examples, and clear guidance using libraries like NumPy and scikit-learn, it’s one of those books you’ll keep dog-eared and bookmarked long after the first read. If you’re serious about mastering machine learning without feeling overwhelmed, this one’s a no-brainer.

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*Product available on Desertcart Nicaragua*
*Store origin: NI*
*Last updated: 2026-03-07*