Movies recommendation and rating prediction using collaborative filtering.
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Updated
Oct 1, 2021 - JavaScript
Movies recommendation and rating prediction using collaborative filtering.
Analysis of Google PlayStore reviews for “League of Legends: Wild Rift” and “Mobile Legends: Bang Bang”
To predict if a customer will like a movie or not depending on his past ratings and preferences using RBMs.
for beginners tutorial
This repo contains the dataset and notebook for the kaggle restaurant reviews five class rating prediction
Designed a system that will use existing yelp data to provide insightful analysis and to assist existing business owners, future business owners to make important decisions about a new business or business expansion.
Movie Rating Prediction based on NETFLIX dataset using Low Rank Matrix factorization technique.
This repository contains the code for the second project for Data Mining classes at the Poznań University of Technology, created by the team Kung Fu Pandas.
This is a repository for our CE7454 Deep Learning for Data Science Project, Group 07
Movie Recommendation Using Matrix Factorization.
An Amazon product recommender system that predicts product ratings and review helpfulness based on linear regression and latent-fact model.
Implemented a model that is capable of predicting a restaurant rating taking into account several factors such as reviews and restaurant facilities. Analysis of review is done based on NLP techniques that include polarity analysis, TF-IDF which are all followed by pre-processing.
This repository holds the dataset and notebooks for the Amazon Books dataset 4 class Rating prediction
Worked on building a predictive model by considering multicollinearity and other Machine learning concepts related to factors or variables using R programming.
A Python Package for Benchmarking Collaborative Filtering Algorithms in Recommendation
Predicting Amazon ratings based on reviews by Text Classification using the Naive Bayes Algorithm.
Dash app on Render about a Dashboard for Sales and Rating Prediction
Employee Rating Prediction using Random Forest and XGBoost in R
This project is an implementation of simple rating prediction systems for items from user
Kaggle competition for a UCSD graduate level CSE class " Recommenders System"
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