/ISLpy

Introduction to Statistical Learning with Python

Primary LanguageJupyter Notebook

ISLpy

Introduction to Statistical Learning with Python

This repo works through the conceptual and applied exercises found in the excellent book An Introduction to Statistical Learning with Applications in R by James, Whitten, Hastie, and Tibshirani. However, instead of R we will be using Python and the requisite libraries.

"This book provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist."

There is also a very good MOOC that accompanies this book that is taught by co-authors and Stanford University professors Trevor Hastie and Rob Tibshirani. Prof's Hastie and Tibshirani also co-authored the canonical Elements of Statistical Learning which is a more advanced treatment of the topics discussed in ISL.

Python libraries

  • pandas
  • numpy
  • statsmodels
  • scikit-learn
  • matplotlib
  • seaborn