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Hands-On Automated Machine Learning

You're reading from   Hands-On Automated Machine Learning A beginner's guide to building automated machine learning systems using AutoML and Python

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788629898
Length 282 pages
Edition 1st Edition
Languages
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Authors (2):
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Umit Mert Cakmak Umit Mert Cakmak
Author Profile Icon Umit Mert Cakmak
Umit Mert Cakmak
Sibanjan Das Sibanjan Das
Author Profile Icon Sibanjan Das
Sibanjan Das
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to AutoML FREE CHAPTER 2. Introduction to Machine Learning Using Python 3. Data Preprocessing 4. Automated Algorithm Selection 5. Hyperparameter Optimization 6. Creating AutoML Pipelines 7. Dive into Deep Learning 8. Critical Aspects of ML and Data Science Projects 9. Other Books You May Enjoy

Summary

In this chapter, we introduced you to the world of neural networks and deep learning. We discussed different activation functions, the structure of a neural network, and demonstrated a feed-forward neural network using Keras.

Deep learning is a topic in itself, and there are several deep learning books with an in-depth focus. The objective of this chapter was to provide you with a head start in exploring deep learning, as it is the next frontier in machine learning automation. We witnessed the power of autoencoders for dimensionality reduction. Also, the CNNs, with their robust feature-processing mechanism, are an essential component for building the automated systems of the future.

We will end our discussion in the next chapter, where we review what we have covered so far, the next steps, and the necessary skills to create a complete machine learning system.

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