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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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Building an object recognizer

In the previous recipe, Training an image classifier using Extremely Random Forests, we used ERFs to train our image classifier. Now that we have trained an ERF model, let's go ahead and build an object recognizer that can recognize the content of unknown images.

Getting ready

In this recipe, we will learn how to use a trained ERF model to recognize the content of unknown images.

How to do it...

Let's see how we can build an object recognizer:

Create a new Python file and import the following packages (the full code is given in...

The rest of the chapter is locked

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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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