resources of FAST-NUCES 2020-2024
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Updated
May 28, 2024 - HTML
resources of FAST-NUCES 2020-2024
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Using the MovieLens dataset, will create a customer recommendation system from scratch using PyTorch.
Pytorch domain library for recommendation systems
A Content Based Filtering Recommender System of current popular movies from Letterboxd based on the tastes of a specific user.
An application that allow the user to log in (and access to all his data), and connect to external distributors, in order to get the coffee generated by a Machine Learning algorithm
LastFM recommendation with sentiment analysis (Bachelor Thesis Project)
Neural collaborative filtering recommendation system on Movie lens 100k dataset
RecTools - library to build Recommendation Systems easier and faster than ever before
The source code of MacGNN, The Web Conference 2024.
Benchmark for Multi-Scenario-Recommendation.
The FranKGraphBench is a Framework to allow KG Aware RSs to be benchmarked in a reproducible and easy to implement manner. It was first created on Google Summer of Code 2023 for Data Integration between DBpedia and some standard RS datasets in a reproducible framework.
A personalized recommendation system and AI Chatbot on streamlit using Zephyr 7B β for online seafood shop: Manettas.
Heart Failure Management System
Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
Content based movie recommendation system
Product Recommender
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