You're reading from Machine Learning Automation with TPOT Build, validate, and deploy fully automated machine learning models with Python

Product type Paperback

Published in May 2021

Publisher Packt

ISBN-13 9781800567887

Length 270 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Author (1):

Dario Radečić

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Table of Contents (14) Chapters

Preface

1. Section 1: Introducing Machine Learning and the Idea of Automation

2. Chapter 1: Machine Learning and the Idea of Automation FREE CHAPTER

3. Section 2: TPOT – Practical Classification and Regression

4. Chapter 2: Deep Dive into TPOT

5. Chapter 3: Exploring Regression with TPOT

6. Chapter 4: Exploring Classification with TPOT

7. Chapter 5: Parallel Training with TPOT and Dask

8. Section 3: Advanced Examples and Neural Networks in TPOT

9. Chapter 6: Getting Started with Deep Learning: Crash Course in Neural Networks

10. Chapter 7: Neural Network Classifier with TPOT

11. Chapter 8: TPOT Model Deployment

12. Chapter 9: Using the Deployed TPOT Model in Production

13. Other Books You May Enjoy

Installing TPOT and setting up the environment

This section discusses the last required step before diving into the practical stuff – installation and environment setup. It is assumed that you have Python 3 installed, either through the standalone installation or through Anaconda.

You will learn how to set up a virtual environment for TPOT for the following scenarios:

Standalone Python
Anaconda

There's no need to read both installation sections, so just pick whichever suits you better. There shouldn't be any difference with regards to installation between operating systems. If you have Python installed as a standalone installation, you have access to pip through the terminal. If you have it installed through Anaconda, you have access to Anaconda Navigator.