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hadryan's Projects

react-spotify icon react-spotify

A music shop Spotify client built with React / Redux 🎀🎺 🎸🎷

readys icon readys

A Speech Analytics Python Tool for Speaking Assessment

real-esrgan icon real-esrgan

Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

realtime icon realtime

Listen to your to PostgreSQL database in realtime via websockets. Built with Elixir.

realtime_pyaudio_fft icon realtime_pyaudio_fft

Realtime audio analysis in Python, using PyAudio and Numpy to extract and visualize FFT features from streaming audio.

rebound icon rebound

A Java library that models spring dynamics and adds real world physics to your app.

recent-stars-2022 icon recent-stars-2022

πŸ”₯πŸ”₯πŸ”₯SLAM, VIsual localization, keypoint detection, Image matching, Pose/Object tracking, Depth/Disparity/Flow Estimation, 3D-graphic, etc. related papers and code

recmetrics icon recmetrics

A library of metrics for evaluating recommender systems

reco4php icon reco4php

Neo4j based Recommendation Engine Framework for PHP

recognize icon recognize

πŸ‘ πŸ‘‚ Smart media tagging for Nextcloud: recognizes faces, objects, landscapes, music genres

recomm icon recomm

Recommended music, series, etc, along with the scripts to generate the lists.

recommend-music icon recommend-music

날씨에 λ”°λ₯Έ μŒμ•… μΆ”μ²œ μ‚¬μ΄νŠΈπŸ˜€

recommendable icon recommendable

A web application that recommends users new music based on explicit feedback.

recommendation-amazon-musical-instrument icon recommendation-amazon-musical-instrument

Applying different recommendation systems, for example, Popularity based recommendation, Single value decomposition, item-item collaborative filtering and user-user based collaborative filtering on Amazon Musical Instrument data to get recommednations for user

recommendation-system icon recommendation-system

This is an attempt to create a recommendation system using Karl Pearson's coefficient and Euclidean's distance

recommendation-system-2 icon recommendation-system-2

Based on the idea of Spotify : a concrete example to understand how graph databases work, with Neo4j. The challenge is to create a music recommendation algorithm, using a very large database of songs (Million Song Dataset) with a graphical interface (Symfony).

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