---
product_id: 422067384
title: "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems"
price: "R1800"
currency: ZAR
in_stock: true
reviews_count: 8
url: https://www.desertcart.co.za/products/422067384-hands-on-machine-learning-with-scikit-learn-keras-and-tensorflow
store_origin: ZA
region: South Africa
---

# End-to-end ML project tracking Advanced neural net architectures TensorFlow & Keras integration Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

**Price:** R1800
**Availability:** ✅ In Stock

## Summary

> 🚀 Elevate your AI game with the ultimate hands-on ML toolkit!

## Quick Answers

- **What is this?** Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- **How much does it cost?** R1800 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.co.za](https://www.desertcart.co.za/products/422067384-hands-on-machine-learning-with-scikit-learn-keras-and-tensorflow)

## Best For

- Customers looking for quality international products

## Why This Product

- Free international shipping included
- Worldwide delivery with tracking
- 15-day hassle-free returns

## Key Features

- • **Uncover Hidden Patterns:** Leverage unsupervised learning techniques like clustering and anomaly detection to extract valuable insights.
- • **Master Real-World ML Projects:** Follow a complete machine learning pipeline using scikit-learn to build practical, deployable models.
- • **Hands-On with TensorFlow & Keras:** Build, train, and optimize neural networks for vision, NLP, and reinforcement learning with industry-standard tools.
- • **Explore Cutting-Edge Neural Networks:** Dive deep into CNNs, RNNs, GANs, transformers, and more to stay ahead in AI innovation.
- • **Challenge Yourself with Practical Exercises:** Engage with real-world problems and advanced exercises that push your skills beyond theory.

## Overview

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is a top-ranked, comprehensive guide that empowers professionals to build intelligent systems through practical projects. Covering everything from classical ML models to advanced neural networks, this book combines clear explanations, real-world exercises, and cutting-edge tools to transform your understanding and application of machine learning.

## Description

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems [Géron, Aurélien] on desertcart.com. *FREE* shipping on qualifying offers. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Review: Great book to learn practical Machine Learning - I have just finished Hands-On ML book and I cannot recommend it enough. I have been working as a Mobile Software Developer for 12 years and now I am thinking about trying something new. I remember some Math and Statistics from school but definitely not enough to get deep into the subject. From my experience, you can read the book and finish all the exercises without understanding any of the Math (although as author points out, it is beneficial if you understand the Math behind it - e.g. to understand why it works, read and implement papers). Book goes into the detail and explains the history of how we got there so it was fairly easy for me to follow and understand majority of the book. I missed this kind of detail from ML courses that I tried. You will also see significant papers explained - something that would be difficult for me to do alone at this point. However, one thing I appreciated the most were the exercises. In ML courses I tried, the exercises were simple and too easy to give you anything. Here it was a real challenge and I have a good feeling about what I learned by doing those exercises. There are also a lot of references for books or papers in case you want to focus on a specific area. One blind spot I am seeing though is focus on Keras/TensorFlow and GCP pipeline whereas the most examples on internet seem to be from PyTorch and AWS as a most popular cloud solution. However, as author points out, if you know one it will be easy for you to switch (I also reimplemented some of the PyTorch projects as part of exercises without too much difficulty). Still, I need to think about it and get some more PyTorch and AWS experience.
Review: Better explanation, better visuals, nice print - I bought three AI books this year and I ended up reading this one so far by Aurelien instead of the other (which was unfortunately in black & white, had misaligned paper cut, etc.). The book by Aurelien Geron (3rd edition) has better explanation, better visual aids, nicer print, etc. One thing I probably would suggest though, is to maybe do a similar code comments style/explanation like what was done in the third book that I got (Deep Learning With Python by Francis Chollet), which I just got but haven't read yet. Some of the code explanation is on the same page/area/line. Convenient. No flipping of pages...

## Features

- Use scikit-learn to track an example ML project end to end
- Explore several models, including support vector machines, decision trees, random forests, and ensemble methods
- Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection
- Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers
- Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #18,139 in Books ( See Top 100 in Books ) #6 in Computer Neural Networks #10 in Python Programming #50 in Artificial Intelligence & Semantics |
| Customer Reviews | 4.7 out of 5 stars 836 Reviews |

## Images

![Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems - Image 1](https://m.media-amazon.com/images/I/81qHV3ACapL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Great book to learn practical Machine Learning
*by A***R on April 4, 2025*

I have just finished Hands-On ML book and I cannot recommend it enough. I have been working as a Mobile Software Developer for 12 years and now I am thinking about trying something new. I remember some Math and Statistics from school but definitely not enough to get deep into the subject. From my experience, you can read the book and finish all the exercises without understanding any of the Math (although as author points out, it is beneficial if you understand the Math behind it - e.g. to understand why it works, read and implement papers). Book goes into the detail and explains the history of how we got there so it was fairly easy for me to follow and understand majority of the book. I missed this kind of detail from ML courses that I tried. You will also see significant papers explained - something that would be difficult for me to do alone at this point. However, one thing I appreciated the most were the exercises. In ML courses I tried, the exercises were simple and too easy to give you anything. Here it was a real challenge and I have a good feeling about what I learned by doing those exercises. There are also a lot of references for books or papers in case you want to focus on a specific area. One blind spot I am seeing though is focus on Keras/TensorFlow and GCP pipeline whereas the most examples on internet seem to be from PyTorch and AWS as a most popular cloud solution. However, as author points out, if you know one it will be easy for you to switch (I also reimplemented some of the PyTorch projects as part of exercises without too much difficulty). Still, I need to think about it and get some more PyTorch and AWS experience.

### ⭐⭐⭐⭐⭐ Better explanation, better visuals, nice print
*by -***L on January 5, 2026*

I bought three AI books this year and I ended up reading this one so far by Aurelien instead of the other (which was unfortunately in black & white, had misaligned paper cut, etc.). The book by Aurelien Geron (3rd edition) has better explanation, better visual aids, nicer print, etc. One thing I probably would suggest though, is to maybe do a similar code comments style/explanation like what was done in the third book that I got (Deep Learning With Python by Francis Chollet), which I just got but haven't read yet. Some of the code explanation is on the same page/area/line. Convenient. No flipping of pages...

### ⭐⭐⭐⭐⭐ Very insightful
*by J***E on January 4, 2026*

Insightful and easy to follow.

## Frequently Bought Together

- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
- AI Engineering: Building Applications with Foundation Models

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*Product available on Desertcart South Africa*
*Store origin: ZA*
*Last updated: 2026-03-02*