Performance-portable geometric search library

This repository contains analysis and exploration of causal and non-causal relationships between genes and phenotypes using embeddings generated from GPT-3.5. The project applies vector analysis, dimensionality reduction, and clustering techniques (K-Means, Hierarchical, and DBSCAN) to uncover potential patterns and insights into causality.

DBSCAN implementation

Clustering USA Weather Stations

Implemented density-based scan clustering Machine Learning model for human brain parcellation and detected over 60 clusters in each brain hemisphere. The model was developed using Matlab.

Indoor PM2.5 source detection algorithm using unsupervised clustering ML method (k-means clustering)

Le clustering consiste à regrouper les données en clusters, où les objets d'un même groupe sont plus similaires entre eux qu'avec ceux des autres groupes.

This repository contains code for a near real-time news clustering and summarization solution using AWS services like Lambda, Step Functions, Kinesis, and Bedrock. It demonstrates how to efficiently process, embed, cluster, and summarize large volumes of news articles to provide timely insights for financial services and other industries.

Wine Industry Market Development: A proof of concept using APIs and Machine Learning for targeted market development inside the wine industry.

DBSCAN and OPTICS clustering algorithms.

Course material for "Dimensionality reduction in Neuroscience"

Clustering of properties in teheran

This project is aimed at leveraging dataset containing > 500K credit card transaction in Europe in 2023 to train a ML model to predict/detect fraudulent transactions.

Interactive courseware module that addresses the theory behind multiple clustering methods and how to apply them to real data sets.

Code examples of point cloud processing in python.

Collection of machine learning exercises developed in Google Colab. This repository covers key ML concepts such as classification, regression, and neural networks, using libraries like TensorFlow and Scikit-learn.

Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms - R package

Final Project for Data mining in which we cretaed a classification system and a regression model

Customer Segmentation using Clustering

📸 Face Clustering Engine developed using OpenCV & DBSCAN, deployed as a Streamlit Web App to deliver uploaded images grouped according to the individual unique faces in them.