PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

Implementation of NAACL 2024 Outstanding Paper "LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models"

Tool for evaluating atmospheric carbon dioxide concentrations as simulated by Earth system models

This repository commits to the application of biostatistics knowledge on clinical, randomized trials and observational studies.

Sub-package of spatstat containing functionality for parametric modelling and inference

Tool for evaluating atmospheric carbon dioxide concentrations as simulated by Earth system models

This project uses the Reaction Time Survey dataset to develop a linear regression model for accurately predicting student reaction times based on various predictors. Tech: R (RStudio)

Global challenge to create Species Distribution Model to predict occurrence of frog species, Litoria fallax, in Australia.

This repository contains some of the time series analysis, diagnostics and forecasting projects I have done.

Objective of this project is to perform predictive assesment on the Gross Domestic Product of India through an inferential analysis of various socio-economic factors to find out which predictors contribute most to the GDP. Various models are compared and Stepwise Regression model is implemented which resulted in 5.7% Test MSE.

Detailed implementation of various time series analysis models and concepts on real datasets.

Using linear regression models to assess the most important aspects of winning baseball

Human Demographic Contributions to the 2004 Death Rate by U.S. State and County modeled with a Random Intercept Mixed Model

Predicting wage in the uswage dataset (Linear Regression). Model Selection, Model Diagnostics etc.

Lending Club's loan data analysis using data cleaning/wrangling to predictive modeling

analysis of stackoverflow developer survey // logistic regression

Working through the book and exercises Pandas for Everyone by Daniel Chen

Model diagnostics based on cumulative residuals (R package) https://kkholst.github.io/gof/