Dario Radecic - Machine Learning Automation with TPOT
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Build, validate, and deploy fully automated machine learning models with Python
Dario Radei
BIRMINGHAMMUMBAI
Copyright 2021 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
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First published: May 2021
Production reference: 1060421
Published by Packt Publishing Ltd.
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ISBN 978-1-80056-788-7
Dario Radei is a full-time data scientist at Neos, in Croatia, a part-time data storyteller at Appsilon, in Poland, and a business owner. Dario has a master's degree in data science and years of experience in data science and machine learning, with an emphasis on automated machine learning. He is also a top writer in artificial intelligence on Medium and the owner of a data science blog called Better Data Science.
Prajjwal is an Electrical Engineering student at Aligarh Muslim University and a member of the AUV-ZHCET club where he works on computer vision. He is the coordinator of the web-dev team at the IEEE student chapter & a mentor at AMU-OSS. Previously, he worked with DeepSource as the developer relation intern for 6 months.
A book is always a collective effort, I owe thanks to Aligarh Muslim University, AUV-ZHCET, DeepSource, my seniors to help me throughout my programming journey. I would also like to show my gratitude to my brother & mentor Roopak & my parents who on every step encouraged me
The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models more cheaply and quickly than with traditional methods.
With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and its associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets.
By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level.
Data scientists, data analysts, and software developers who are new to machine learning and want to use it in their applications will find this book useful. This book is also for business users looking to automate business tasks with machine learning. Working knowledge of the Python programming language and a beginner-level understanding of machine learning are necessary to get started.
, Machine Learning and the Idea of Automation, covers a brief introduction to machine learning, the difference between classification and regression tasks, an overview of automation and why it is needed, and the machine learning options in the Python ecosystem.
, Deep Dive into TPOT, provides an in-depth overview of what TPOT is and isn't, how it is used to handle automation in machine learning, and what types of tasks it can automate. This chapter also sees you set up the programming environment.
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