Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

Framework for correlating two or more well logs using feature vectors generated from CNN's in Pytorch

Joblib-like interface for parallel GPU computations (e.g. data preprocessing)

📊 30 Days of Data Science is a daily challenge to guide you through Data Science essentials. From basics to advanced, this repo offers clear examples, practical exercises, and resources to help you master Data Science, one day at a time. Whether you're new or refining your skills, this challenge has something for you. Join the journey now! 🚀

A machine learning exercise using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.

Spam SMS Detection Project implemented using NLP & Transformers. DistilBERT - a hugging face Transformer model for text classification is used to fine-tune to best suit data to achieve the best results. Multinomial Naive Bayes achieved an F1 score of 0.94, the model was deployed on the Flask server. Application deployed in Google Cloud Platform

A step-by-step guide to master various aspects of Joblib for parallel computing in Python

A GitHub WebCrawler

A machine learning project to predict smoking status (Smoker/Non-Smoker) using health and lifestyle data. It includes data preprocessing, model training, evaluation, visualizations, and FastAPI-based deployment, supporting CI/CD and multiple datasets for robustness.

PyPOLAR is a Python-based app for analyzing polarization-resolved microscopy data to measure molecular orientation and order in biological samples

predict the winning horse with supervised machine learning models (lucky to have 100% accuracy on small test data)

A Proximal Policy Optimization Approach to Detect Spoofing in Algorithmic Trading

An IA model that detects whether a given verse is from the Bible or not

A Regression Model that predicts a fish's weight based on its specie, length, width & height.

Python scripts to download, process, and analyze the New York City Taxi and Limousine Commission (TLC) Trip Record Data dataset

A basic malware detector using Machine Learning

A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn

A bot designed to answer live trivia game questions.

Machine Learning Project for recommendations of music genre based on age and gender

Python scripts that scrape US gas prices