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sunitab55/README.md

πŸ’« About Me:

Hey I'm Subarna! I'm doing my master's in Data Science at UT Austin. Coming from an analytical background, I like to use numbers, math and data science in all kinds of unconventional settings. For example, in my last internship my manager casually told me that the department has a lot of septic system permit applications to go through beacuse they are manually approved. So, I came up with a proposal to use machine learning models to automate a part of this process!

I'm also like the perspective of being a penguins enthusiast waddling through the field of Data Science, and Machine Learning! I did my undergrad in Pure Math working on research topics in Representation Theory, Combinatorics and Number Theory!

Fun Stuff

There is a statistical feature called the "Bhattacharyya distance" and it happens to be my last name. It measures the similarity between two probability distributions! https://en.wikipedia.org/wiki/Bhattacharyya_distance

I say my birthday is well defined because it's the only date in a year that is the combination of second largest prime date and second largest prime month. :D

🌐 Socials:

LinkedIn

πŸ’» Tech Stack:

R Python Java Anaconda MicrosoftSQLServer Matplotlib NumPy Pandas Plotly PyTorch scikit-learn Scipy TensorFlow

πŸ“Š GitHub Stats:




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  1. mnist_classifier mnist_classifier Public

    learning to deploy a model :P

    Jupyter Notebook

  2. Spotify-Recommends Spotify-Recommends Public

    Testing out recommenders! πŸ₯³πŸŽΉ

    Python

  3. Geospatial-Analysis Geospatial-Analysis Public

    Analysis on EV πŸ˜‡βš‘ stations across the United States

    R

  4. Undergrad-Thesis Undergrad-Thesis Public

    Study of Young's Latices πŸ€“πŸ“’

  5. Covid-19-Project Covid-19-Project Public

    Exploring SQL and Tableau πŸ˜πŸ˜πŸ“’

  6. Data-Science-Interview-Resources Data-Science-Interview-Resources Public

    Forked from rbhatia46/Data-Science-Interview-Resources

    A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

    1