Machine Learning with Python Cookbook

Practical Solutions from Preprocessing to Deep Learning

Nonfiction, Computers, Advanced Computing, Programming, Data Modeling & Design, Database Management, Data Processing
Cover of the book Machine Learning with Python Cookbook by Chris Albon, O'Reilly Media
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Chris Albon ISBN: 9781491989333
Publisher: O'Reilly Media Publication: March 9, 2018
Imprint: O'Reilly Media Language: English
Author: Chris Albon
ISBN: 9781491989333
Publisher: O'Reilly Media
Publication: March 9, 2018
Imprint: O'Reilly Media
Language: English

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics.

Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications.

You’ll find recipes for:

  • Vectors, matrices, and arrays
  • Handling numerical and categorical data, text, images, and dates and times
  • Dimensionality reduction using feature extraction or feature selection
  • Model evaluation and selection
  • Linear and logical regression, trees and forests, and k-nearest neighbors
  • Support vector machines (SVM), naïve Bayes, clustering, and neural networks
  • Saving and loading trained models
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or numerical data, model selection, and dimensionality reduction and many other topics.

Each recipe includes code that you can copy and paste into a toy dataset to ensure that it actually works. From there, you can insert, combine, or adapt the code to help construct your application. Recipes also include a discussion that explains the solution and provides meaningful context. This cookbook takes you beyond theory and concepts by providing the nuts and bolts you need to construct working machine learning applications.

You’ll find recipes for:

More books from O'Reilly Media

Cover of the book Head First PMP by Chris Albon
Cover of the book SharePoint Apps with LightSwitch by Chris Albon
Cover of the book Google Analytics by Chris Albon
Cover of the book Ruby Cookbook by Chris Albon
Cover of the book Building Maintainable Software, Java Edition by Chris Albon
Cover of the book eBay: The Missing Manual by Chris Albon
Cover of the book Perl in a Nutshell by Chris Albon
Cover of the book Understanding Compression by Chris Albon
Cover of the book Data Science from Scratch by Chris Albon
Cover of the book Droid 2: The Missing Manual by Chris Albon
Cover of the book Windows 2000 Pro: The Missing Manual by Chris Albon
Cover of the book SUSE Linux by Chris Albon
Cover of the book SQL Tuning by Chris Albon
Cover of the book Mobile HTML5 by Chris Albon
Cover of the book Applied Software Project Management by Chris Albon
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy