Statistics and Quantitative Analysis Library for C++. Squall provides a set of robust, high-performance and easy to use tools for managing, manipulating & reshaping datasets, calculating statistics, aggregating data, extracting subsets and much more. Squall contains 4 header files only and is easy to implement into any existing C++ project.

This project explores the application of Long Short-Term Memory (LSTM) networks in predicting household power consumption. Using data collected at one-minute intervals, we demonstrate how LSTM can be leveraged for accurate forecasting.

Machine Learning with Python: Halliburton Landmark Learning

Assignments done in my STAT:440 Data Management Using R

Analyzed athletic sales data using Pandas, employing techniques like concatenation, joins, groupby, and pivot tables to identify top-performing regions, retailers, and product categories. The project highlighted advanced data combination and reshaping skills to uncover key sales insights.

R coaching session materials for epidemiologists