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Machine Learning with scikit-learn Quick Start Guide

You're reading from Machine Learning with scikit-learn Quick Start Guide

Product type Book

Published in Oct 2018

Publisher Packt

ISBN-13 9781789343700

Pages 172 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Kevin Jolly

Table of Contents (10) Chapters

Preface

Introducing Machine Learning with scikit-learn

Predicting Categories with K-Nearest Neighbors

Predicting Categories with Logistic Regression

Predicting Categories with Naive Bayes and SVMs

Predicting Numeric Outcomes with Linear Regression

Classification and Regression with Trees

Clustering Data with Unsupervised Machine Learning

Performance Evaluation Methods

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Implementing linear regression in scikit-learn

In this section, you will implement your first linear regression algorithm in scikit-learn. To make this easy to follow, the section will be divided into three subsections, in which you will learn about the following topics:

Implementing and visualizing a simple linear regression model in two dimensions
Implementing linear regression to predict the mobile transaction amount
Scaling your data for a potential increase in performance

Linear regression in two dimensions

In this subsection, you will learn how to implement your first linear regression algorithm, in order to predict the amount of a mobile transaction by using one input feature: the old balance amount of the account...

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Authors (1)

Kevin Jolly

Kevin Jolly is a formally educated data scientist with a master's degree in data science from the prestigious King's College London. Kevin works as a statistical analyst with a digital healthcare start-up, Connido Limited, in London, where he is primarily involved in leading the data science projects that the company undertakes. He has built machine learning pipelines for small and big data, with a focus on scaling such pipelines into production for the products that the company has built. Kevin is also the author of a book titled Hands-On Data Visualization with Bokeh, published by Packt. He is the editor-in-chief of Linear, a weekly online publication on data science software and products.

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