Data Science Explorations

I explore the world of machine learning, deep learning, computer vision, natural language processing, MLOps.

Exploring the internet

Mainly this is a repo to learn from, implement and keep track of a plethora of tutorials (mostly small) present on the internet (Youtube, Medium articles, other articles). Here is how my workflow looks like:

1. I notice a good small doable tutorial.
2. I immediately file a Github issue with the description containing the link of the tutorial.
   • The issue labels are assigned according to the contents of the tutorial
3. Now I start working on re-implementing this tutorial, and push the small project folder to this repo, closing the issue.

Exploring myself

The other kind of exploration I do is when I have a small idea to implement with an experimental mindset. Again I follow the same workflow:

1. I get an awesome idea
2. I immediately file a Github issue with the description of my idea.
   • The issue labels are assigned according to general topic the idea is going to explore.
3. Now I start working on implementing this idea, and push the small project folder to this repo, closing the issue.

Note

• There is a top level README.md containing the completed exploration.
• Along with this, there is a separate README.md for each small explorations.