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  • Book Overview & Buying Hands-On Automated Machine Learning
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Hands-On Automated Machine Learning

Hands-On Automated Machine Learning

By : Sibanjan Das, Umit Mert Cakmak
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Hands-On Automated Machine Learning

Hands-On Automated Machine Learning

By: Sibanjan Das, Umit Mert Cakmak

Overview of this book

AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions.
Table of Contents (10 chapters)
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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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Hands-On Automated Machine Learning
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