Presentation created for the Atlanta Developers' Conference, September 17, 2022, hosted at Kennesaw State University in Marietta, GA.
Many Machine Learning, AI and Data Science/Analytics tasks require some level of data analysis, experimentation, and visualization. If you’re relatively new to these topics there is a significant learning curve in not only the concepts, but often also the tools required to complete the tasks. The goal of this session is to introduce you to common free open-source software (FOSS) used by ML and DS practitioners so that your toolbox is a bit more complete.
At a bare minimum:
- Clone this repo
- Create a Python 3 virtual environment
- Activate the new environment
- Install the dependencies listed in
requirements.py3into your virtual environment - Execute the command
jupyter labfrom with in the environment, from the repo root
Depending on your platform, you will always get a link in the console output to open the notebook server in your browser of choice; some platforms will just launch the default browser and open the link for you in a new tab. Any further dependencies are installed via pip as you progress through the notebooks, or you can pull the package lists from those cells and install using your favorite python package manager.
Included in LICENSE.md - have fun!
This is intended to be a mostly unmaintained codebase once the conference is over, but if there are some glaring issues with using it please do open an issue and a PR if you have a fix. Thanks!