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pradhyumn/README.md
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Hey! How's everything going?

💫About Me

💻 Education : Graduate student at NYU specializing in Machine Learning applications. Undergraduate from IIT Kharagpur with 3+ years of experience in the Aerospace Industry (Airbus).

💼 Experience : C++ and Python software developer, good at Machine Learning Algorithms, intermediate at Pytorch, Pandas and Pyspark.

🔭 My unique quality : I am good at understanding the Mathematics behind everything, have also qualified the RMO (Regional Mathematics Olympiad) in 2013 and always look at things from an algorithmic perspective. I am also very good at Probability & Stochastic Processes.

🌱 I am learning : Generative AI, Large-language models, Natural Language Processing, Computer Vision, Diffusion Models.

📫 Best way to contact : E-mail me at pradhyumn.bhale@nyu.edu

🌎 Visit my webpage at: https://pradhyumn.github.io

Technologies & Tools

📊GitHub Stats

Pradhyumn's GitHub Stats

Pinned

  1. RL-based-Active-Portfolio-Management RL-based-Active-Portfolio-Management Public

    Implementing a deep reinforcement learning framework for Financial Portfolio Management.

    Python 7

  2. Factory-Plant-Simulation Factory-Plant-Simulation Public

    Simulation of the workflow in a factory plant between production and plant workers using buffers and multi-threading in C++

    C++ 6 1

  3. Disturbance-Prediction-UAV Disturbance-Prediction-UAV Public

    Disturbance prediction with stable pose control for unmanned vehicles (American Control Conference 2022)

    C++ 4

  4. Music-recommender-system Music-recommender-system Public

    Latent-factor based recommendation system (ALS) for music recommendation along with a single-machine implementation for faster training.

    Jupyter Notebook 4

  5. Isolated-sign-language-recognition Isolated-sign-language-recognition Public

    Deep Learning project on the Google- Isolated Sign Language Recognition

    Jupyter Notebook 6

  6. Portfolio-default-rate Portfolio-default-rate Public

    Mining actual bank data from Italy to calculate the portfolio default rate. The model intends to provide better predictions of the one-year probability of default (PD) for prospective borrowers.

    Jupyter Notebook