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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

Engagement model for a typical data science project

When you start to learn anything new, or build on your existing knowledge, it's important to understand the background of things and how the story has evolved over time, knowing that the current trends were a natural evolution of conventional reporting, business intelligence (BI), and analytics. That's why the initial chapters walked you through the background and fundamentals of ML pipelines, such as data preprocessing, automated algorithm selection, and hyperparameter optimization.

Due to the highly experimental nature of AutoML pipelines, there were many concepts explained together with their practical examples.

The ideas that advanced analytics and ML use to solve problems are not necessarily new, but they are only usable now as people have easy access to cheaper hardware and software resources. More advanced technologies...

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