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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

Dive into Deep Learning

The next step in artificial intelligence (AI) is more about automation. In this book, we have covered some of the fundamentals of Automated machine learning (AutoML). There is one more area of AI that has just begun showing up in multiple use cases and is required to be applied extremely for automation. This area of the AI landscape is known as deep learning (DL). DL is at the tipping point of what machines can do. It can do more than machine learning (ML), with ease and with better precision. A DL algorithm can learn the critical features of a dataset by itself, can adjust the weights to create a better model, and much more. The applications of DL networks are extensive.

With the advent of Deep learning, researchers and practitioners in the field of image, speech, and video recognition, are seeing some actionable results. It has helped AI to get close...

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