neural_collaborative_filtering | Neural Collaborative Filtering | Recommender System library

by hexiangnan Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | neural_collaborative_filtering Summary

neural_collaborative_filtering is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Recommender System, Deep Learning applications. neural_collaborative_filtering has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However neural_collaborative_filtering build file is not available. You can download it from GitHub.

Neural Collaborative Filtering

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Security

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Reuse

Support

neural_collaborative_filtering has a medium active ecosystem.

It has 1597 star(s) with 626 fork(s). There are 31 watchers for this library.

It had no major release in the last 6 months.

There are 49 open issues and 22 have been closed. On average issues are closed in 18 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of neural_collaborative_filtering is current.

Quality

neural_collaborative_filtering has 0 bugs and 29 code smells.

Security

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

neural_collaborative_filtering code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

neural_collaborative_filtering is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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

Installation instructions, examples and code snippets are available.

neural_collaborative_filtering saves you 225 person hours of effort in developing the same functionality from scratch.

It has 549 lines of code, 21 functions and 5 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Evaluate the model
Evaluate a single item
Calculate the CDG of a given rank
Returns the hit ratio of a given ranklist item
Construct an MLP model
Parse command line arguments
Load a pretraining model
Generate training instances

Get all kandi verified functions for this library.

neural_collaborative_filtering Key Features

No Key Features are available at this moment for neural_collaborative_filtering.

neural_collaborative_filtering Examples and Code Snippets

No Code Snippets are available at this moment for neural_collaborative_filtering.

Community Discussions

Trending Discussions on neural_collaborative_filtering

How to use initializations.normal in Keras2.2.4

what does it take to convert theano backend to tensorflow backend with Keras?

QUESTION

How to use initializations.normal in Keras2.2.4

Asked 2019-Nov-21 at 03:17

I learn He's NCF code from Github, He use Keras 1.0.7 and Theano 0.8.0. These codes can't run in my Keras 2.2.4, like the "initializations". How to change them?

...

ANSWER

Answered 2019-Nov-21 at 03:17

Keras2 API is not backwards compatible with Keras API and you are likely to have more problems like that coming up. If you have a chance, I suggest you install Keras 1.0.7 to run this example.

If you feed adventurous though, please take a look at the Embedding layer definition in Keras2 docs:

Source https://stackoverflow.com/questions/58966643

QUESTION

what does it take to convert theano backend to tensorflow backend with Keras?

Asked 2019-Mar-26 at 16:28

I'm trying to convert https://github.com/hexiangnan/neural_collaborative_filtering

The library uses theano as a backend, how involved is it to change to tensorflow backend?
It uses keras as well

I only see import theano.tensor as T when I search for theano and import

Would it be as simple as changing the import statement to tensorflow?

some of import statements that look relavant are:

...

ANSWER

Answered 2019-Mar-26 at 16:28

You also need to change the keras backend parameters. This can be done in two ways as described in the documentation one is changing the keras configuration file and the other is changing the environment variable at the top of your script

Source https://stackoverflow.com/questions/55360795

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

Vulnerabilities

No vulnerabilities reported

Install neural_collaborative_filtering

Docker quickstart guide can be used for evaluating models quickly. Build a keras-theano docker image.
Ubuntu Installation
Mac OSX Installation
Windows Installation

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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