Fortran Statistics and Machine Learning Library

A modern Fortran statistical library.

Significant Network Interval Mining

Quantitative research tool analyzing stock performance around US Thanksgiving. 354 stocks, 8,293 observations (2000-2024). Statistical significance testing included.

Customer base analysis is concerned with using the observed past purchase behavior of customers to understand their current and likely future purchase patterns. More specifically, as developed in Schmittlein et al. (1987), customer base analysis uses data on the frequency, timing, and dollar value of each customer's past purchases

AI Firewall and guardrails for LLM-based Elixir applications

Analysis of 2.2 million Realtor.com listings using Python and machine learning to uncover U.S. real estate market patterns. The project identifies market segments, predicts property prices, and reveals regional trends, providing data-driven insights for real estate professionals and investors.

This repository is a fork of a repository originally created by Lucas Descause. It is the codebase used for my Master's dissertation "Reinforcement Learning with Function Approximation in Continuing Tasks: Discounted Return or Average Reward?" which was also an extension of Luca's work.

Statistical tests in Rust

High-performance statistical testing and regression for Polars DataFrames, powered by Rust.

Yeast TMT data - 3 different carbon sources (from Gygi lab) analyzed with PAW pipeline and MaxQuant

MATLAB functions for Beta distribution test

Analytical workflow for Superstore Business Insights: identifies key profitability drivers via statistical tests and quantile regression. Includes data cleaning, hypothesis testing, model checks, and actionable recommendations from SampleSuperstoreClean.csv.

Multivariate analysis (MVA) of high dimensional heterogeneous data

Analysis of proportions using Anscombe transform

Quantium has had a data partnership with a supermarket brand for the last few years that provide transactional and customer data. You are an analyst within the Quantium analytics team and are responsible for delivering highly valued data analytics and insights to help the business make strategic decisions.

This repository contains all about the proposed solutions to the assignments that I was required to complete as part of the Quantium Data Analytics Virtual Experience Program. 📊📈📉👨‍💻

This repository will include Python | Jupyter-Notebook statistical testing | tests and analysis. Highly useful for in depth data analysis & model development.