Table of Contents for
Introduction to Machine Learning with Python

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Introduction to Machine Learning with Python by Sarah Guido Published by O'Reilly Media, Inc., 2016
  1. Cover
  2. nav
  3. Introduction to Machine Learning with Python
  4. Introduction to Machine Learning with Python
  5. Preface
  6. 1. Introduction
  7. 2. Supervised Learning
  8. 3. Unsupervised Learning and Preprocessing
  9. 4. Representing Data and Engineering Features
  10. 5. Model Evaluation and Improvement
  11. 6. Algorithm Chains and Pipelines
  12. 7. Working with Text Data
  13. 8. Wrapping Up
  14. Index
  15. About the Authors
  16. Colophon

About the Authors

Andreas Müller received his PhD in machine learning from the University of Bonn. After working as a machine learning researcher on computer vision applications at Amazon for a year, he joined the Center for Data Science at New York University. For the last four years, he has been a maintainer of and one of the core contributors to scikit-learn, a machine learning toolkit widely used in industry and academia, and has authored and contributed to several other widely used machine learning packages. His mission is to create open tools to lower the barrier of entry for machine learning applications, promote reproducible science, and democratize the access to high-quality machine learning algorithms.

Sarah Guido is a data scientist who has spent a lot of time working in start-ups. She loves Python, machine learning, large quantities of data, and the tech world. An accomplished conference speaker, Sarah attended the University of Michigan for grad school and currently resides in New York City.