Descriptive analytics project using kprototypes to discover project profiles from a dataset of 15,000+ projects.

a visualization method for neural data

nQuantCpp includes top 6 color quantization algorithms for visual c++ producing high quality optimized images.

nQuantGpp includes top 10 color quantization algorithms for g++ producing high quality optimized images.

Comprehensive dimensionality reduction and cluster analysis toolset

A flexible, fast and scalable python library for Self-Organizing Maps

Python, unsupervised machine learning

DocClusterizer is a Java desktop application designed to analyze and cluster documents based on their content similarity. The application utilizes Lucene and Tika libraries to process various file extensions such as txt, pdf, docx, and pptx.

Utilizing KMeans clustering, this project segments customers for targeted marketing and analysis. Developed on Google Colab, it imports datasets from Kaggle, performs data analysis, preprocessing, and model building, providing actionable insights for businesses.

Prodigy-Mall Customer Segmentation

"GitHub project for finding campgrounds and remote workspaces. Discover, organize, and enhance your mobile experience!"

Unsupervised Machine Learning Model

About Unsupervised Machine Learning-Netflix Recommender recommends Netflix movies and TV shows based on a user's favorite movie or TV show. It uses a a K-Means Clustering model to make these recommendations. These models use information about movies and TV shows such as their plot descriptions and genres to make suggestions.

Unsupervised Machine Learning-Netflix Recommender recommends Netflix movies and TV shows based on a user's favorite movie or TV show. It uses a a K-Means Clustering model to make these recommendations. These models use information about movies and TV shows such as their plot descriptions and genres to make suggestions.

The project aims to combat loneliness using OkCupid's dataset. Leveraging unsupervised ML techniques, it'll develop a recommendation algorithm to enhance profile matching based on compatibility, improving success rates in finding meaningful connections on the platform.

Unsupervised clustering of globus pallidus and striato-thalamic regions

Customer Purchase Analysis

We build end-to-end unsupervised solution for customer segmentation using PyCaret deploy the model using Streamlit.

Python re-implementation of the (constrained) spectral clustering algorithms used in Google's speaker diarization papers.

This is a project which uses Data Science, Machine learning to predict the stock movements, minimize the risk and maximise gains of portfolio using fama-french factors and many other models.Also the sentiment towards stocks are also monitored using sentiment analysis. Garch Model is used to predict the volatility and movements for intraday trading.