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)

🚀 A flexible Python library for easy handling and conversion of Hierarchical, Tabular, and Serialized data formats.

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.

A GitHub WebCrawler

A Proximal Policy Optimization Approach to Detect Spoofing in Algorithmic Trading

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

An efficient text classification pipeline for email subjects, leveraging NLP techniques and Multinomial Naive Bayes. Easily preprocess data, train the model, and categorize new email subjects. Ideal for NLP enthusiasts and those building practical email categorization systems using Python.

A basic malware detector using Machine Learning

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

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

Predicts which telecom customers are likely to churn with 95% accuracy using real-world data features from usage, billing, and support data. Implements Sturges-based binning, one-hot encoding, stratified 80/20 train-test split, and a two-level ensemble pipeline with soft voting. Achieves 94.60% accuracy, 0.8968 AUC, 0.8675 precision, 0.7423 recall.

A bot designed to answer live trivia game questions.

This project aims to detect and classify fake news using Natural Language Processing (NLP) and Machine Learning techniques. The model is trained to identify whether a news article is real or fake based on its content.

magic-wormholing pickled objects made simple

StockSage is a production-ready RESTful API built with FastAPI and Docker to serve machine learning models. It allows users to send stock data and receive price predictions using the Prophet model. Designed for scalability, it follows best practices in API deployment, containerization, and production model serving.

Python utility for fetching any historical data using caching. Suitable for news, posts, weather, etc.

Python scripts that scrape US gas prices

This project is a Paddy Crop Disease Detection System that uses machine learning to identify diseases in paddy (rice) leaves. Farmers can upload an image of a paddy leaf, and the system will predict whether the leaf is healthy or affected by a specific disease