movie-recommendation-system | Movie recommendation system in python | Recommender System library
kandi X-RAY | movie-recommendation-system Summary
kandi X-RAY | movie-recommendation-system Summary
movie-recommendation-system is a Python library typically used in Artificial Intelligence, Recommender System applications. movie-recommendation-system has no bugs, it has no vulnerabilities and it has low support. However movie-recommendation-system build file is not available. You can download it from GitHub.
Movie recommendation system in python that uses uses the lightfm recommender system library.
Movie recommendation system in python that uses uses the lightfm recommender system library.
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Quality
Security
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Support
movie-recommendation-system has a low active ecosystem.
It has 18 star(s) with 13 fork(s). There are 3 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of movie-recommendation-system is current.
Quality
movie-recommendation-system has 0 bugs and 0 code smells.
Security
movie-recommendation-system has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
movie-recommendation-system code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
movie-recommendation-system 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.
Reuse
movie-recommendation-system releases are not available. You will need to build from source code and install.
movie-recommendation-system has no build file. You will be need to create the build yourself to build the component from source.
movie-recommendation-system saves you 7 person hours of effort in developing the same functionality from scratch.
It has 22 lines of code, 1 functions and 1 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed movie-recommendation-system and discovered the below as its top functions. This is intended to give you an instant insight into movie-recommendation-system implemented functionality, and help decide if they suit your requirements.
- Sample the prediction .
Get all kandi verified functions for this library.
movie-recommendation-system Key Features
No Key Features are available at this moment for movie-recommendation-system.
movie-recommendation-system Examples and Code Snippets
No Code Snippets are available at this moment for movie-recommendation-system.
Community Discussions
Trending Discussions on movie-recommendation-system
QUESTION
Wrapping dplyr filter in function results in "Error: Result must have length 4803, not 3"
Asked 2019-Nov-11 at 15:17
I'm learning R for data analysis and using this Kaggle dataset. Following the movie recommendation script works, but when I try to generalize a dplyr code by making it a function I get an error:
I've tried troubleshooting some. It looks like the code stops at the filter and mutate functions.
The following works and gives the expected output.
...ANSWER
Answered 2019-Nov-11 at 15:16The problem is that you cannot use character strings to identify variables inside filter and mutate.
The easiest way to solve your problem is to use filter_at and mutate_at:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install movie-recommendation-system
You can download it from GitHub.
You can use movie-recommendation-system 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.
You can use movie-recommendation-system 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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