Best Practices on Recommendation Systems
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Updated
May 16, 2024 - Python
Best Practices on Recommendation Systems
A TensorFlow recommendation algorithm and framework in Python.
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms
⚡ A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize
A Lighting Pytorch Framework for Recommendation System, Easy-to-use and Easy-to-extend.
This is a new deep learning model for recommender system, which we called PHD
🔱 Some recognized algorithms[Decision Tree, Adaboost, Perceptron, Clustering, Neural network etc. ] of machine learning and pattern recognition are implemented from scratch using python. Data sets are also included to test the algorithms.
Finding recommendations between them all. Work in progress.
Code for RecSys'19 paper: Leveraging Post-click Feedback for Content Recommendations
A real-time news scraping and recommendation system
[PY]thon [R]ec[O]mmender [S]ystems library
Board game recommendation engine
A book recommendations application that works on the Dash framework and implements content based filtering using TF-IDF and cosine similarity.
A lightweight recommendation algorithm framework based on LycorisNet.
MIT xPRO Data Science Course Movie Recommendations Case Study
Movie Recommendation Engine based on a K-Means clustering algorithm of IMDB public data. Node server for user interface.
Recommends movies based on user input and a a pre-trained NMF-model with a browser-based user interface (Flask). Optionally outputs movie trailers for recommendations from YouTube.
Contextual Movie Recommender System built on mobile with the aim of showing interest based movies from the huge amount of data based on rating of user and critics which would be crawled from the specified website. Recommender System are primarily directed towards individuals who lack sufficient personal experience or competence to evaluate the po…
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