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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

You're reading from   Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits A practical guide to implementing supervised and unsupervised machine learning algorithms in Python

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838826048
Length 384 pages
Edition 1st Edition
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Author (1):
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Tarek Amr Tarek Amr
Author Profile Icon Tarek Amr
Tarek Amr
LinkedIn
Tarek Amr has 8 years of experience in data science and machine learning. After finishing his postgraduate degree at the University of East Anglia, he worked in a number of startups and scale-up companies in Egypt and the Netherlands. This is his second data-related book. His previous book covered data visualization using D3.js. He enjoys giving talks and writing about different computer science and business concepts and explaining them to a wider audience. He can be reached on Twitter at @gr33ndata. He is happy to respond to all questions related to this book. Feel free to get in touch with him if any parts of the book need clarification or if you would like to discuss any of the concepts here in more detail.
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Supervised Learning
2. Introduction to Machine Learning FREE CHAPTER 3. Making Decisions with Trees 4. Making Decisions with Linear Equations 5. Preparing Your Data 6. Image Processing with Nearest Neighbors 7. Classifying Text Using Naive Bayes 8. Section 2: Advanced Supervised Learning
9. Neural Networks – Here Comes Deep Learning 10. Ensembles – When One Model Is Not Enough 11. The Y is as Important as the X 12. Imbalanced Learning – Not Even 1% Win the Lottery 13. Section 3: Unsupervised Learning and More
14. Clustering – Making Sense of Unlabeled Data 15. Anomaly Detection – Finding Outliers in Data 16. Recommender System – Getting to Know Their Taste 17. Other Books You May Enjoy

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Authors (1)

Profile icon Tarek Amr
Tarek Amr
LinkedIn icon Github icon
Tarek Amr has 8 years of experience in data science and machine learning. After finishing his postgraduate degree at the University of East Anglia, he worked in a number of startups and scale-up companies in Egypt and the Netherlands. This is his second data-related book. His previous book covered data visualization using D3.js. He enjoys giving talks and writing about different computer science and business concepts and explaining them to a wider audience. He can be reached on Twitter at @gr33ndata. He is happy to respond to all questions related to this book. Feel free to get in touch with him if any parts of the book need clarification or if you would like to discuss any of the concepts here in more detail.
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See other products by Tarek Amr

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