Unified embedding generation and search engine. Also available on cloud - cloud.marqo.ai

Session-weighted recommendation system in Python

Integration with (approximate) nearest neighbors libraries for scikit-learn + clustering based on with kNN-graphs.

PostgreSQL vector database extension for building AI applications

The GPU-powered AI application database. Get your app to market faster using the simplicity of SQL and the latest NLP, ML + LLM models.

This repository contains code for building a K-Nearest Neighbors (KNN) model to predict diabetes based on patient data. Includes data cleaning, hyperparameter tuning, and evaluation metrics.

Tokenize and convert sample text data into vectors using BERT. Load the vector representation of the text to OpenSearch and use kNN for semantic search

This project focuses on analysing the performance of various Machine Learning models available in python's scikit-learn package when trying to predict wine classification

Thesis work. A mobile application for recipe recommendations.

Proyecto de investigación en ML para identificar factores genéticos en pronóstico de lesiones pre-tumorales. Aprendizaje no supervisado para discernir perfiles genéticos distintivos entre grupos de buen y mal pronóstico, mejorando detección y tratamiento temprano del cáncer.

Open-source AI library (audio to text, simple NLP, and common algorithms)

User experience for subscription model of Financial Application

JVector: the most advanced embedded vector search engine

Routines for generating, manipulating, parsing, importing vector embeddings into Postgres tables

Course Material for Artificial Intelligence and Machine Learning - Unit 2 @ Computer Science Dept, Sapienza

Given the list of locations of customers who frequently order Pizza we want to find out optimal locations of Pizza Parlours where they should be opened.

Este repositório contém conteúdo do trabalho da disciplina de Inteligência Artificial do curso de Ciências da Computação - UNIFEI.

DINO Explorer: A tool to explore DINO embeddings.

This is a Science and Technology Society (STS) of Sarasota-Manatee Counties that shows the data from a series of NASA STELLA-Q2 Spectrometer readings on a number of vegetative species with calculations of NDVI to differentiate species using Decision Tree logic and Knn from the mean end member data.