Resources

Prob & Stats

• Khan Academy
• Coursera Statistical Inference

Python

We will use Python in this course. Although Python knowledge is not a prerequisite, the expectation is that you have experience with programming and can pick it up pretty quickly.

• Learning Python [Schafer] Java 2 Python 3: A guide to learning Python by comparing it to Java - Hunter Schafer Note: Only useful if you know Java.
• Python for R users
• Python for Matlab users
• Learn Python in Y Minutes
• Software Carpentry Python Novice Lesson
• Very comprehensive Python cheat sheet

Machine Learning

Online Reading References

All resources on this page are optional and are here for you if you need extra help or want to dive deeper into the material. Most of the materials listed here are available for free and are online, while a few physical textbooks are also referenced. Resources that start with [square brackets] are referenced on the calendar.

Machine Learning Texts:

• [ESL] The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed. - Trevor Hastie, Robert Tibshirani, Jerome Friedman
• [Duame] A Course on Machine Learning - Hal Duame
• [Murphy] Machine Learning: A Probabilistic Probabilistic Perspective - Kevin Murphy
• [Bishop] Pattern Recogntion and Machine Learning - Chris Bishop
• [FoML] Foundations of Machine Learning - Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar

Data Science:

• [PyDS] Python for Data Science - Jake VanderPlas
• Berkeley Principles and Techniques of Data Science - UC Berkeley Data 100 Course