CANtropy: Time Series Feature Extraction-Based Intrusion Detection Systems for Controller Area Networks

Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

An analysis on the murder patterns in India from 2015-2021. It looks into the patterns in motives and the possible socio economic factor affecting murder in India.

This project aims to understand and predict a car's fuel efficiency based on its characteristics. I have built a multiple linear regression model using stats models and scikit-learn.

Binary Classification: Predicting whether Airbnb listings will have a high booking rate.

This repository contains the projects I worked on during my Data Science Internship at CodSoft. The projects cover various domains and demonstrate different aspects of data science, including data preprocessing, feature engineering, model training, and evaluation.

Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.

The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt

This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.

Creating a course curriculum by extracting skills that are in demand at the job market from job vacancies web-scrapped from indeed web-portal and apply clustering algorithms to group/segment skills into courses.

End-to-End Machine Learning project I made as a machine learning intern @ Mentorness

A platform enables sharing diverse knowledge, but similarly worded questions are common. We use NLP techniques to identify duplicate questions, enhancing user experience by making it easier to find high-quality answers.

All Statistics concepts

Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖

Automated Time Series Forecasting

Up to 90% accuracy with just 5 features using KNN algorithm and PCA for feature engineering. The dataset contained less than 1000 observations. The model's accuracy could be improved using more observations, further hyperparameter optimization and feature engineering

Comprehensive notes and code on Python, data analysis, visualization, machine learning, and deep learning from my data science learning journey.