GSB 544: Data Science and Machine Learning with Python
Preface
This text was created for the Cal Poly course “GSB 544: Data Science and Machine Learning with Python” by Dr. Kelly Bodwin and Dr. Hunter Glanz. Some parts of the material and text are borrowed from Dr. Emily Robinson’s R course and Dr. Dennis Sun’s python course
This text is not meant to be a complete course or textbook by itself; rather, think of it as “long-form” class slides. We will summarize the main concepts in each chapter, show you examples, point you to more in-depth readings from outside sources, and ask you to try out short tasks in python as you go.
How to Use This Text
Watch out sections contain things you may want to look out for - common errors, etc.
Note sections contain clarification points (anywhere I would normally say “note that ….). Make sure to read them to avoid any common pitfalls or misconceptions.
Additional Resources
References or additional readings may come from the following texts:
- Python Data Science Handbook by Jake VanderPlas
- Python for Data Analysis by Wes McKinney
- Principles of Data Science by Dennis Sun
For extra practice with python programming, we recommend the DataQuest interactive tutorials or working through some lessons on Python for Everybody.