Machine Learning with scikit-learn Quick Start Guide
Classification, regression, and clustering techniques in Python
Published on 23. September 2024
172 pages
978-1-78934-737-1 (ISBN)
Description
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Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
3,18 MB
ISBN-13
978-1-78934-737-1 (9781789347371)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Kevin Jolly
Machine Learning with scikit-learn Quick Start Guide
Classification, regression, and clustering techniques in Python
Book
10/2018
Packt Publishing
€39.10
Shipment within 3-4 weeks
Person
Jolly Kevin :
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.
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.
Content
Table of Contents
Introducing Machine Learning with scikit-learn
Predicting categories with K-Nearest Neighbours
Predicting categories with Logistic Regression
Predicting categories with Naive Bayes and SVMs
Predicting numeric outcomes with Linear Regression
Classification & Regression with Trees
Clustering data with Unsupervised Machine Learning
Performance evaluation methods
Introducing Machine Learning with scikit-learn
Predicting categories with K-Nearest Neighbours
Predicting categories with Logistic Regression
Predicting categories with Naive Bayes and SVMs
Predicting numeric outcomes with Linear Regression
Classification & Regression with Trees
Clustering data with Unsupervised Machine Learning
Performance evaluation methods
