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Hands-On Automated Machine Learning

You're reading from  Hands-On Automated Machine Learning

Product type Book
Published in Apr 2018
Publisher Packt
ISBN-13 9781788629898
Pages 282 pages
Edition 1st Edition
Languages
Authors (2):
Sibanjan Das Sibanjan Das
Profile icon Sibanjan Das
Umit Mert Cakmak Umit Mert Cakmak
Profile icon Umit Mert Cakmak
View More author details
Toc

Table of Contents (10) Chapters close

Preface 1. Introduction to AutoML 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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