SIGIR2020_NICF | Neural Interactive Collaborative Filtering , SIGIR

 by   guyulongcs Python Version: Current License: No License

kandi X-RAY | SIGIR2020_NICF Summary

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

            kandi-support 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.

            kandi-Quality Quality

              SIGIR2020_NICF has no bugs reported.

            kandi-Security Security

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

            kandi-License 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.

            kandi-Reuse 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


            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.


            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 .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
          • HTTPS


          • CLI

            gh repo clone guyulongcs/SIGIR2020_NICF

          • sshUrl


          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link