This repo contains a set of AI and Data Science tutorials in Python curated and revised by me. I modified most of the tutorials to add more instructions and make sure they work well in configured virtual environments. Many thanks to the tutorial authors and other contributors. See the README in each tutorial folder for details.

I organize the tutorials into four folders:

• ai for AI tutorials
• ds for Data Science tutorials
• ml for machine learning/deep learning tutorials
• other for code on things like data processing, one-off tricks, etc.

Setup

Each tutorial may have different version requirements for certain packages. So, each tutorial will use a separate virtual environment.

For some tutorials, you may need to set API keys. You need to add a .env file and include the API keys as follows (see my blog post on Manage Environment Variables in Python Projects):

OPENAI_API_KEY=sk-proj-xxxx
LANGCHAIN_API_KEY=ls__69650xxxx
REPLICATE_API_TOKEN=r8_W0V3rJxxx

To run each tutorial, you need to do the following at the root of this project - I use document_clustering tutorial as an example:

cd document_clustering
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Then, you can use VSCode code . to open the notebooks.