ml-unsupervised

Introduction

This repository contains the materials for the course on applied unsupervised machine learning.

Course Developers: see our guidelines page if contributing materials.

These materials are released under a CC BY 4.0 license.

Steps for course developers

• Create a Python virtual environment

   python3 -m venv .venv

source .venv/bin/activate

• Install all requirements

   pip install -r requirements.txt

• Install Quarto and VS Code

• Change the .qmd files

• Render using quarto

quarto render

• Commit files in _freeze folder and any other .qmd files changed

chmod 755 gitshell.sh
./gitshell.sh

Contact

Soumya Banerjee

[email protected]