Machine Learning Courses

A repository containing Introduction to Machine Learning Course, Advanced Machine Learning Course, and Deep Learning Notes and Projects.

Setup

We use Python, Conda, and the usual machine learning packages for this class.

You can also use Anaconda for Windows + VSCode, Collabera, etc.

  sudo pacman -S python3 python-pip pythonA
  yay -S python-conda jupyterlab jupyter-notebook
  # Create a conda environment named ml for machine learning
  conda create -n "ml"
  sudo conda init bash
  # Re-exec bash, enter the venv
  bash
  conda activate ml
  # Get all the ml packages
  conda install --yes numpy scipy pandas scikit-learn matplotlib seaborn
  # Update conda
  conda update -n base conda
  # To use the system env versus the conda 'base' env on startup
  conda config --set auto_activate_base false

See: github.com/bbullman/dotfiles for more installation instructions on various OS and environments.

Directories

• The Class Notes directory is a structured markdown wiki using Obsidian.
• Books contains free resources including the ISLP
• Machine Learning contains labs, exercises, case studies, and datasets for the base class
• Machine Learning (Advanced) contains labs, exercises, case studies, for the advanced class
• Deep Learning contains labs, exercises, case studies, for the deep learning class