MovieRecommender | Movie Recommender Based on Matrix Factorization | Recommender System library

by junlulocky Python Version: Current License: No License

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kandi X-RAY | MovieRecommender Summary

MovieRecommender is a Python library typically used in Artificial Intelligence, Recommender System applications. MovieRecommender has no bugs, it has no vulnerabilities and it has low support. However MovieRecommender build file is not available. You can download it from GitHub.

This is a Movie Recommender System Based on Matrix Factorization, train and test on the movielens100k.mat dataset. The dataset for this project comes from MovieLens (It consists of 100,000 ratings from 1000 users on 1700 movies. The rating values go from 0 to 5. The dataset is split into train and test data, around 95,000 and 5,000 ratings respectively. With all the parameters well set, a RMSE of around 0.8008 (actually MSE according to the formula provided) can be achieved.

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MovieRecommender has a low active ecosystem.

It has 4 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

MovieRecommender has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MovieRecommender is current.

Quality

MovieRecommender has no bugs reported.

Security

MovieRecommender has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

MovieRecommender does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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MovieRecommender releases are not available. You will need to build from source code and install.

MovieRecommender has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed MovieRecommender and discovered the below as its top functions. This is intended to give you an instant insight into MovieRecommender implemented functionality, and help decide if they suit your requirements.

Matrix factorization factorization
Generate test data .
Test the recommender .

Get all kandi verified functions for this library.

MovieRecommender Key Features

No Key Features are available at this moment for MovieRecommender.

MovieRecommender Examples and Code Snippets

No Code Snippets are available at this moment for MovieRecommender.

Community Discussions

Trending Discussions on MovieRecommender

VSCode terminal shows incorrect python version and path, launching terminal from anaconda works perfectly

QUESTION

VSCode terminal shows incorrect python version and path, launching terminal from anaconda works perfectly

Asked 2020-Feb-03 at 13:03

I have been stuck on this one problem for hours now and believe I have tried everything outside of throwing my computer out of the window.

I have a virtual environment set up on Anaconda using python version 3.7 and Django version 2.1. If I activate this virtual environment from Anaconda everything works smoothly.

...

ANSWER

Answered 2019-Feb-07 at 23:32

I just ran into the same problem. Try switching out of the powershell terminal to the windows terminal. Then restart. It should restart with the anaconda terminal. If that does not work you could:

First change the default terminal from within Visual Code to the CMD terminal instead of Powershell. Add the following code to a batch file.

Source https://stackoverflow.com/questions/54582361

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install MovieRecommender

You can download it from GitHub.
You can use MovieRecommender like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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