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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
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Concepts
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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
Umit Mert Cakmak is a data scientist at IBM, where he excels at helping clients solve complex data science problems, from inception to delivery of deployable assets. His research spans multiple disciplines beyond his industry and he likes sharing his insights at conferences, universities, and meet-ups.
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Sibanjan Das Sibanjan Das
Author Profile Icon Sibanjan Das
Sibanjan Das
Sibanjan Das is a Business Analytics and Data Science consultant. He has extensive experience in implementing predictive analytics solutions in Business Systems and IoT. An enthusiastic and passionate professional about technology and innovation, he has the passion for wrangling with data since early days of his career. Sibanjan holds a Masters IT degree with major in Business Analytics from Singapore Management University and holds several industry certifications such as OCA, OCP and CSCMS.
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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

Technical requirements

Check the requirements.txt file for libraries to be installed to run code examples in GitHub for this chapter.

All the code examples can be found in the Chapter 04 folder in GitHub.

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Authors (2)

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Profile icon Das
Das
Akhil Das is a senior software developer at Sigmoid primarily focusing on distributed computing, real-time analytics, performance optimization, and application scaling problems using a wide variety of technologies such as Apache Spark and Mesos, among others. He contributes actively to the Apache Spark project and is a regular speaker at big data conferences and meetups, MesosCon 2015 being the most recent one.
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Profile icon Mert Cakmak
Mert Cakmak
Umit Mert Cakmak is a data scientist at IBM, where he excels at helping clients solve complex data science problems, from inception to delivery of deployable assets. His research spans multiple disciplines beyond his industry and he likes sharing his insights at conferences, universities, and meet-ups.
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