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Artificial Intelligence with Python Cookbook

You're reading from Artificial Intelligence with Python Cookbook Proven recipes for applying AI algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6

Product type Paperback

Published in Oct 2020

Publisher Packt

ISBN-13 9781789133967

Length 468 pages

Edition 1st Edition

Languages

Python

Tools

PyTorch

Concepts

Artificial Intelligence

Authors (2):

Ritesh Kumar

Ben Auffarth

View More author details

Table of Contents (13) Chapters

Preface

1. Getting Started with Artificial Intelligence in Python

2. Advanced Topics in Supervised Machine Learning FREE CHAPTER

3. Patterns, Outliers, and Recommendations

4. Probabilistic Modeling

5. Heuristic Search Techniques and Logical Inference

6. Deep Reinforcement Learning

7. Advanced Image Applications

8. Working with Moving Images

9. Deep Learning in Audio and Speech

10. Natural Language Processing

11. Artificial Intelligence in Production

12. Other Books You May Enjoy

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Technical requirements

In this chapter, we mainly use the following:

scikit-learn, as before
Keras, as before
Lifetimes (https://lifetimes.readthedocs.io/), a library for customer lifetime value
tensorflow-probability (tfp; https://www.tensorflow.org/probability)

You'll find the code for this chapter on GitHub at https://github.com/PacktPublishing/Artificial-Intelligence-with-Python-Cookbook/tree/master/chapter04.

The rest of the chapter is locked

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Authors (2)

Kumar

Kumar

Ritesh Kumar is an experienced researcher with a demonstrated history of working on various industry-sponsored projects mainly on Data Analysis, Machine Learning, and Intelligent Instrumentation. Currently Ritesh is associated with the University of Hertfordshire.

See other products by Kumar

Ben Auffarth

Ben Auffarth

Ben Auffarth is a full-stack data scientist with more than 15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds and thousands of transactions per day, and trained language models on a large corpus of text documents. He co-founded and is the former president of Data Science Speakers, London.

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