SIGIR2020_NICF | Neural Interactive Collaborative Filtering , SIGIR

by guyulongcs Python Version: Current License: No License

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

kandi X-RAY | SIGIR2020_NICF Summary

SIGIR2020_NICF is a Python library. SIGIR2020_NICF has no bugs, it has no vulnerabilities and it has low support. However SIGIR2020_NICF build file is not available. You can download it from GitHub.

Neural Interactive Collaborative Filtering, SIGIR 2020

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Quality

Security

License

Reuse

Support

SIGIR2020_NICF has a low active ecosystem.

It has 5 star(s) with 0 fork(s). There are 1 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 125 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SIGIR2020_NICF is current.

Quality

SIGIR2020_NICF has no bugs reported.

Security

SIGIR2020_NICF has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

SIGIR2020_NICF 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

SIGIR2020_NICF releases are not available. You will need to build from source code and install.

SIGIR2020_NICF 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 SIGIR2020_NICF and discovered the below as its top functions. This is intended to give you an instant insight into SIGIR2020_NICF implemented functionality, and help decide if they suit your requirements.

Write a dict of key - value pairs
Creates latent variables
Multihead attention
Feed forward layer
Normalize input tensor
Configure OpenAI
Get the rank without MPI
Log message to the current thread
Log all output formats
Example demo
Configure OpenAI logging
Return a dump of the current configuration
Argument parser
Create a TensorFlow model
Create a new model without distribution
Calculate DCG for the given episode and uid
Perform a step policy
Decorator to profile a function
Builds the model
Context manager for context manager
Train the model
Get objects from name_space
Get current working directory
Log all values in a dictionary
Resets the logger
Set random seed

Get all kandi verified functions for this library.

SIGIR2020_NICF Key Features

No Key Features are available at this moment for SIGIR2020_NICF.

SIGIR2020_NICF Examples and Code Snippets

No Code Snippets are available at this moment for SIGIR2020_NICF.

Community Discussions

No Community Discussions are available at this moment for SIGIR2020_NICF.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install SIGIR2020_NICF

You can download it from GitHub.
You can use SIGIR2020_NICF 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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