Python machine learning course

https://ualberta-rcg.github.io/python-machine-learning

Getting the notebooks

To get the notebooks that make up this course, you can either use them in Google Colab, or download them to your own computer.

Opening notebooks on Colab:

• Go to File->Open notebook
• Select “Github” tab
  • Organization: ualberta-rcg (important: press enter)
  • Repository: ualberta-rcg/python-machine-learning
  • Choose the notebook you want

Here is a direct link to the first notebook in Colab: https://colab.research.google.com/github/ualberta-rcg/python-machine-learning/blob/main/notebooks/01-intro-classification.ipynb

Getting notebooks on your computer:

Either use git to clone the repository at Github:

git clone https://github.com/ualberta-rcg/python-machine-learning.git

… or click here to download from your browser: https://github.com/ualberta-rcg/python-machine-learning/archive/main.zip

… or run the following in a Jupyter notebook:

# Warning, might overwrite notebooks if they exist
import os, urllib.request, zipfile
def get_notebooks():
  repo = 'python-machine-learning'
  branch = 'main'
  repo_url = 'https://github.com/ualberta-rcg/{}'.format(repo)
  zip_url = '{}/archive/{}.zip'.format(repo_url, branch)
  zip_file = '{}.zip'.format(repo)
  output_dir = '{}-{}'.format(repo, branch)
  if os.path.exists(zip_file): return
  urllib.request.urlretrieve(zip_url, zip_file)
  with zipfile.ZipFile(zip_file) as zip_ref:
    zip_ref.extractall()
  print('Downloaded to {} in {} directory'.format(output_dir, os.getcwd()))
get_notebooks()

Installing dependencies

To install the dependencies (not needed on Colab), run the following at the command line (preferably in a python virtual environment):

pip install tensorflow keras jupyter matplotlib pandas scikit-learn graphviz

Or in a Jupyter notebook:

!pip install tensorflow keras jupyter matplotlib pandas numpy scikit-learn graphviz