gpu-recommmendation-engine | GPU powered recommendation system
kandi X-RAY | gpu-recommmendation-engine Summary
kandi X-RAY | gpu-recommmendation-engine Summary
gpu-recommmendation-engine is a Java library. gpu-recommmendation-engine has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
This file was created by IntelliJ IDEA 10.5.2 for binding GitHub repository.
This file was created by IntelliJ IDEA 10.5.2 for binding GitHub repository.
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Quality
Security
License
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Support
gpu-recommmendation-engine has a low active ecosystem.
It has 4 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
gpu-recommmendation-engine has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of gpu-recommmendation-engine is current.
Quality
gpu-recommmendation-engine has no bugs reported.
Security
gpu-recommmendation-engine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
gpu-recommmendation-engine 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
gpu-recommmendation-engine releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed gpu-recommmendation-engine and discovered the below as its top functions. This is intended to give you an instant insight into gpu-recommmendation-engine implemented functionality, and help decide if they suit your requirements.
- Performs a factorization
- Run the kernel based on the number of features
- Finds the exe size
- Calculate the average rating for a specific item
- Converts a feature matrix to a matrix
- Main launcher
- Performs the kernel computation
- Initializes the instructions array
- Initializes the array with the specified size
- Initialize a set
- Creates a 64 - bit hash
- Generate 64 - bit hash
- MurmurHashHash algorithm
- Run the kernel
- Binary search A
- Determines whether a value contains a given number
- Hash two sets
- Calculate the kernel
Get all kandi verified functions for this library.
gpu-recommmendation-engine Key Features
No Key Features are available at this moment for gpu-recommmendation-engine.
gpu-recommmendation-engine Examples and Code Snippets
No Code Snippets are available at this moment for gpu-recommmendation-engine.
Community Discussions
No Community Discussions are available at this moment for gpu-recommmendation-engine.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install gpu-recommmendation-engine
You can download it from GitHub.
You can use gpu-recommmendation-engine like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the gpu-recommmendation-engine component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
You can use gpu-recommmendation-engine like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the gpu-recommmendation-engine component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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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