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Machine Learning with scikit-learn Quick Start Guide

You're reading from Machine Learning with scikit-learn Quick Start Guide Classification, regression, and clustering techniques in Python

Product type Paperback

Published in Oct 2018

Publisher Packt

ISBN-13 9781789343700

Length 172 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Author (1):

Kevin Jolly

View More author details

Table of Contents (10) Chapters

Preface

1. Introducing Machine Learning with scikit-learn

2. Predicting Categories with K-Nearest Neighbors FREE CHAPTER

3. Predicting Categories with Logistic Regression

4. Predicting Categories with Naive Bayes and SVMs

5. Predicting Numeric Outcomes with Linear Regression

6. Classification and Regression with Trees

7. Clustering Data with Unsupervised Machine Learning

8. Performance Evaluation Methods

9. Other Books You May Enjoy

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Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Python Machine Learning Blueprints - Second Edition
Alexander Combs

ISBN: 9781788994170

Understand the Python data science stack and the algorithms in use
Apply machine learning techniques to real-world applications
Explore the power of Tensorflow and Keras using complex datasets
Get up and running with topics like NLP, regression, classification, recommendation systems, and Bayesian techniques
Learn to scale up a project using PySpark and build a chatbot
Delve into advanced concepts like Computer Vision, Neural Networks and Deep learning

scikit-learn Cookbook
Trent Hauck

ISBN: 9781783989485

Address algorithms of various levels of complexity and learn how to analyze data at the same time
Handle common data problems such as feature extraction and missing data
Understand...

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Authors (1)

Jolly

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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