Recommender systems are the systems that are designed to recommend things to the user based on many different factors

Related tags

Recommender SystemsMachine-Learning-Recommendation-System
Overview

Machine-Learning-Recommendation-System

Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest.

Why the Recommendation system?

  1. Benefits users in finding items of their interest.
  2. Help item providers in delivering their items to the right user.
  3. Identity products that are most relevant to users.
  4. Personalized content.
  5. Help websites to improve user engagement.

What can be Recommended?

There are many different things that can be recommended by the system like movies, books, news, articles, jobs, advertisements, etc. Netflix uses a recommender system to recommend movies & web-series to its users. Similarly, YouTube recommends different videos. There are many examples of recommender systems that are widely used today.

Owner
Happy N. Monday
Wavelet Transform | Machine Learning | Computer Vision | Deep Learning | Image Processing | AI
Happy N. Monday
GitHub Repository
Pytorch domain library for recommendation systems

TorchRec (Experimental Release) TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale

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Code for KHGT model, AAAI2021

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32 Nov 29, 2022
Recommender systems are the systems that are designed to recommend things to the user based on many different factors

Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filte

Happy N. Monday 3 Feb 15, 2022
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.

RecList is an open source library providing behavioral, "black-box" testing for recommender systems.

Jacopo Tagliabue 375 Dec 30, 2022
This library intends to be a reference for recommendation engines in Python

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Yikun Xian 197 Dec 28, 2022
Collaborative variational bandwidth auto-encoder (VBAE) for recommender systems.

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Çağrı Karadeniz 7 Mar 12, 2022
This is our Tensorflow implementation for "Graph-based Embedding Smoothing for Sequential Recommendation" (GES) (TKDE, 2021).

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Cloud-based recommendation system

This project is based on cloud services to create data lake, ETL process, train and deploy learning model to implement a recommendation system.

Yi Ding 1 Feb 02, 2022
Group-Buying Recommendation for Social E-Commerce

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EXEMPLO DE SISTEMA ESPECIALISTA PARA RECOMENDAR SERIADOS EM PYTHON

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NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIA’s GPUs.

NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in

420 Jan 04, 2023
Bundle Graph Convolutional Network

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55 Dec 25, 2022
A tensorflow implementation of the RecoGCN model in a CIKM'19 paper, titled with "Relation-Aware Graph Convolutional Networks for Agent-Initiated Social E-Commerce Recommendation".

This repo contains a tensorflow implementation of RecoGCN and the experiment dataset Running the RecoGCN model python train.py Example training outp

xfl15 30 Nov 25, 2022
Incorporating User Micro-behaviors and Item Knowledge 59 60 3 into Multi-task Learning for Session-based Recommendation

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ciecus 38 Dec 05, 2022
Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks

Bi-TGCF Tensorflow Implementation of BiTGCF： Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks. in CIKM20

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