---
product_id: 148887041
title: "Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition"
price: "552 Lei"
currency: RON
in_stock: true
reviews_count: 13
url: https://www.desertcart.ro/products/148887041-python-machine-learning-machine-learning-and-deep-learning-with-python
store_origin: RO
region: Romania
---

# Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

**Price:** 552 Lei
**Availability:** ✅ In Stock

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- **What is this?** Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
- **How much does it cost?** 552 Lei with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.ro](https://www.desertcart.ro/products/148887041-python-machine-learning-machine-learning-and-deep-learning-with-python)

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## Description

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition [Raschka, Sebastian, Mirjalili, Vahid] on desertcart.com. *FREE* shipping on qualifying offers. Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

Review: Good for learning about machine learning, needs development on deep learning - I have not finished this book and I just reached chapter 16, but here are my key takeaways for this book: 1. Everything before chapter 13, before the book fully gets into deep learning and TensorFlow, are great. With already some background in python for data analysis (I have also taken the Andrew Ng's Coursera course on Machine Learning), this book supplements my knowledge greatly. The biggest highlight I would say is that it introduces you JUST ENOUGH concepts for you to understand how everything works. In addition, the contents are structured really well, too. If I were to rate this section of the book, I would give 10/10 although it would be better to have some exercises, you can always practice using Kaggle datasets. 2. Since chapter 13 when the book gets into deep learning, things get worse a little bit... The contents are still good in general, however the connections between contents might not be the case. The connections between contents are important for new learners because that helps them to understand how A leads to B and then leads to C. Here, I found the actual TensorFlow documentation a really good material to review along with the book. After reviewing those documentations, coming back to this book allows me to comprehend much more than reading the first time. In addition, if you are not careful enough, the deep learning sections also seems to have accuracy issues with its contents that could confuse people. Even though I have not finished the book, I would give 9/10 for everything I have read for deep learning.
Review: Both practical and complete with theory - It is rare to find a book that covers the topic in ML to a considerable extent. Further, this books contains practical, working examples of ML that are easy to understand and related theory. Great contribution to the learning content in ML.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #142,555 in Books ( See Top 100 in Books ) #51 in Computer Neural Networks #58 in Natural Language Processing (Books) #84 in Python Programming |
| Customer Reviews | 4.5 4.5 out of 5 stars (492) |
| Dimensions  | 7.5 x 1.74 x 9.25 inches |
| Edition  | 3rd ed. |
| ISBN-10  | 1789955750 |
| ISBN-13  | 978-1789955750 |
| Item Weight  | 2.87 pounds |
| Language  | English |
| Print length  | 770 pages |
| Publication date  | December 12, 2019 |
| Publisher  | Packt Publishing |

## Images

![Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition - Image 1](https://m.media-amazon.com/images/I/61bttGCBLUL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Good for learning about machine learning, needs development on deep learning
*by T***Y on June 20, 2020*

I have not finished this book and I just reached chapter 16, but here are my key takeaways for this book: 1. Everything before chapter 13, before the book fully gets into deep learning and TensorFlow, are great. With already some background in python for data analysis (I have also taken the Andrew Ng's Coursera course on Machine Learning), this book supplements my knowledge greatly. The biggest highlight I would say is that it introduces you JUST ENOUGH concepts for you to understand how everything works. In addition, the contents are structured really well, too. If I were to rate this section of the book, I would give 10/10 although it would be better to have some exercises, you can always practice using Kaggle datasets. 2. Since chapter 13 when the book gets into deep learning, things get worse a little bit... The contents are still good in general, however the connections between contents might not be the case. The connections between contents are important for new learners because that helps them to understand how A leads to B and then leads to C. Here, I found the actual TensorFlow documentation a really good material to review along with the book. After reviewing those documentations, coming back to this book allows me to comprehend much more than reading the first time. In addition, if you are not careful enough, the deep learning sections also seems to have accuracy issues with its contents that could confuse people. Even though I have not finished the book, I would give 9/10 for everything I have read for deep learning.

### ⭐⭐⭐⭐⭐ Both practical and complete with theory
*by C***E on May 4, 2025*

It is rare to find a book that covers the topic in ML to a considerable extent. Further, this books contains practical, working examples of ML that are easy to understand and related theory. Great contribution to the learning content in ML.

### ⭐⭐⭐⭐ The python code won’t work with the wrong package versions
*by A***N on August 24, 2023*

I have started to read the first chapter and I have found that the book code just don’t run if you don’t have the correct packages in the Python interpreter. Use the following packages versions for python 3.9.13: NumPy 1.21.2 SciPy 1.7.0 Scikit-learn 1.0 Matplotlib 3.4.3 pandas 1.3.2

## Frequently Bought Together

- Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
- Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

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*Product available on Desertcart Romania*
*Store origin: RO*
*Last updated: 2026-03-08*