I'm a Data Scientist who has been building ML/DL models, Automation and Data Manipulation tools, Pipelines and more using Python...
๐ปLove Coding:
- ML/DL models that not only aims to be high performance but also highly efficient, clean and scalable,
- Programs that cover all the fundamental stages of end-to-end pipelines namely data collection, preprocessing, model building, output distribution,
- Applying widely used tech stack and frameworks to every single project (e.g., Docker, Cloud Services, MLFlow etc.) when possible,
- Out of box solutions that bring novel perspective to the problem at hand,
- Somebody else's work and making a few tweak to it to see if it can serve to my purpose.
๐Love Learning:
- How state of the art algorithms can be built from scratch,
- What and how other open source frameworks can be implemented various kinds of problems to make them even more efficient,
- Better ways to make a piece of code clean, more appealing and reusable,
- How a piece of information can be presented in the best way possible.
Pandas | Numpy
Tensorflow | PyTorch | Scikit-Learn
Docker | FastAPI | MLFlow
Linux | MacOS | Windows
Regex | Levenstein Distance