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scikit-learn Cookbook - Second Edition

You're reading from  scikit-learn Cookbook - Second Edition

Product type Book
Published in Nov 2017
Publisher Packt
ISBN-13 9781787286382
Pages 374 pages
Edition 2nd Edition
Languages
Author (1):
Trent Hauck Trent Hauck
Profile icon Trent Hauck

Table of Contents (13) Chapters

Preface 1. High-Performance Machine Learning – NumPy 2. Pre-Model Workflow and Pre-Processing 3. Dimensionality Reduction 4. Linear Models with scikit-learn 5. Linear Models – Logistic Regression 6. Building Models with Distance Metrics 7. Cross-Validation and Post-Model Workflow 8. Support Vector Machines 9. Tree Algorithms and Ensembles 10. Text and Multiclass Classification with scikit-learn 11. Neural Networks 12. Create a Simple Estimator

Loading data from the UCI repository

The first dataset we will load is the Pima Indians diabetes dataset. This will require access to the internet. The dataset is available thanks to Sigillito V. (1990), UCI machine learning repository (https://archive.ics.uci.edu/ml/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data), Laurel, MD at Johns Hopkins University, applied physics laboratory.

The first thing in your mind if you are an open source veteran is, what is the license/permission to this database? This is a very important issue. The UCI repository has a use policy that requires citation of the database whenever we are using it. We are allowed to use it but we must give them proper credit for their great help and provide a citation.

How to do it...

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