Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Original implementation of the EMD (empirical model discrepancy) model comparison criterion

In this ML project i have used Natural language processing (NLP) techniques and other data preprocessing techniques to feed my Machine Learning Algorithm a good data, and deploy it using flask.

EvalML is an AutoML library written in python.

Rational kernel-based interpolation for complex-valued frequency response functions [arXiv:2307.13484]

Integration of a specific module for Hidden Markov Model Comparison

Fit and compare complex models reliably and rapidly. Advanced nested sampling.

Lightweight and modular MLOps library targeted at small teams or individuals

Variable Selection with Knockoffs

🌹[ICML 2024] Selecting Large Language Model to Fine-tune via Rectified Scaling Law

Regression model building and forecasting in R

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

A personal project where logistic regression is used to predict if a student dropped out.

Metalearning for Hyperparameter Optimization

Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

Inspired by personal curiosity and a 2023 Hackathon challenge (won in the ‘Most Polished’ category). This project investigates the impact of large language models like ChatGPT on entry-level roles in tech. Demonstrated skills include data cleaning, data wrangling, data analysis, and modeling, using tools such as Python, APIs, Polars, and Hvplot.

Search for a model and corresponding hyperparameters that best model your data

Model BIC posterior probability