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Python Machine Learning Cookbook

You're reading from Python Machine Learning Cookbook Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets

Product type Paperback

Published in Mar 2019

Publisher Packt

ISBN-13 9781789808452

Length 642 pages

Edition 2nd Edition

Languages

Python

Tools

Pandas

Concepts

Deep Learning

Authors (2):

Giuseppe Ciaburro

Prateek Joshi

View More author details

Table of Contents (18) Chapters

Preface

1. The Realm of Supervised Learning FREE CHAPTER

2. Constructing a Classifier

3. Predictive Modeling

4. Clustering with Unsupervised Learning

5. Visualizing Data

6. Building Recommendation Engines

7. Analyzing Text Data

8. Speech Recognition

9. Dissecting Time Series and Sequential Data

10. Analyzing Image Content

11. Biometric Face Recognition

12. Reinforcement Learning Techniques

13. Deep Neural Networks

14. Unsupervised Representation Learning

15. Automated Machine Learning and Transfer Learning

16. Unlocking Production Issues

17. Other Books You May Enjoy

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The Realm of Supervised Learning

In this chapter, we will cover the following recipes:

Array creation in Python
Data preprocessing using mean removal
Data scaling
Normalization
Binarization
One-hot encoding
Label encoding
Building a linear regressor
Computing regression accuracy
Achieving model persistence
Building a ridge regressor
Building a polynomial regressor
Estimating housing prices
Computing the relative importance of features
Estimating bicycle demand distribution

You have been reading a chapter from

Python Machine Learning Cookbook - Second Edition

Published in: Mar 2019

Publisher: Packt

ISBN-13: 9781789808452

© 2019 Packt Publishing Limited All Rights Reserved

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Authors (2)

Giuseppe Ciaburro

Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).

See other products by Giuseppe Ciaburro

Joshi

Joshi

Vijay Joshi is a full stack web developer having more than a decade of experience in working with PHP and JavaScript.

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