organised by Vancouver School of AI
Date: 9 October 2018
Instead of working in R, as in the book, we will do the applications in Python.
It is recommended that you use either Google Colab or Jupyter Notebook.
Google Colab: Introduction to Python
The meetup covers Chapter 1 and 2 from the book, An Introduction to Statistical Learning. The book can be downloaded here, but has been added to this repo, here, for convenience.
The book gives R application code snippets. However, we will be working in Python. The Python code snippets for the book can be found here.
Due Date: Sunday, 21 October @ midnight (PST)
Challenge: Explore a dataset of your choice and document your most interesting findings. Use the Python exploration functions discussed in the meetup (e.g. the summarizing and visualizing functions).
Check out the Applied section under 2.4 Exercises in An Introduction to Statistical Learning for inspiration.
Everyone is encouraged to participate!
The winning submission should ideally contain:
- interesting, well-motivated, findings
- documentation explaining your exploration
To submit, post your submission's repository link on the # coding_challenge Slack channel (on the Vancouver School of AI workspace) before the due date.
The core content was created by the authors of An Introduction to Statistical Learning.
Chapters 1 and 2, the focus of this meetup, has been summarised by: