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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

Product type Paperback

Published in Apr 2018

Publisher Packt

ISBN-13 9781788629898

Length 282 pages

Edition 1st Edition

Languages

Python

Tools

Assemble

Concepts

Machine Learning

Authors (2):

Umit Mert Cakmak

Sibanjan Das

View More author details

Table of Contents (10) Chapters

Preface

1. Introduction to AutoML

2. Introduction to Machine Learning Using Python FREE CHAPTER

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

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Linear regression

Let's begin our triple W session with linear regression first.

What is linear regression?

It is the traditional and most-used regression analysis. It is studied rigorously and used widely for practical purposes. Linear regression is a method for determining the relationship between a dependent variable (y) and one or more independent variables (x). This derived relationship can be used to predict an unexplained y from observed x's. Mathematically, if x is an independent variable (commonly known as the predictor) and y is a dependent variable (also known as the target), the relationship is expressed as follows:

Where m is the slope of line, b is the intercept of the best-fit regression line, and...

You have been reading a chapter from

Hands-On Automated Machine Learning

Published in: Apr 2018

Publisher: Packt

ISBN-13: 9781788629898

© 2018 Packt Publishing Limited All Rights Reserved

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Authors (2)

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.

See other products by Das

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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