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Machine Learning Automation with TPOT

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

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781800567887
Length 270 pages
Edition 1st Edition
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Author (1):
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Dario Radečić Dario Radečić
Author Profile Icon Dario Radečić
Dario Radečić
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Toc

Table of Contents (14) Chapters Close

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

Section 2: TPOT – Practical Classification and Regression

This section provides a deep dive into what TPOT is, what it isn't, how it is used to handle automation in machine learning, and what types of tasks TPOT can automate. This section also shows how to install TPOT and the environment setup in general.

This section contains the following chapters:

  • Chapter 2, Deep Dive into TPOT
  • Chapter 3, Exploring before Regression
  • Chapter 4, Exploring before Classification
  • Chapter 5, Parallel Training with TPOT and Dask
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