Restricted-Boltzmann-Machine | An Numpy implementation of RBM | Machine Learning library

by FengZiYjun Python Version: Current License: No License

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kandi X-RAY | Restricted-Boltzmann-Machine Summary

Restricted-Boltzmann-Machine is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Numpy applications. Restricted-Boltzmann-Machine has no bugs, it has no vulnerabilities and it has low support. However Restricted-Boltzmann-Machine build file is not available. You can download it from GitHub.

(The first column is the input. Other columns are reconstructed outputs.).

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Restricted-Boltzmann-Machine has a low active ecosystem.

It has 6 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

Restricted-Boltzmann-Machine has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Restricted-Boltzmann-Machine is current.

Quality

Restricted-Boltzmann-Machine has no bugs reported.

Security

Restricted-Boltzmann-Machine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Restricted-Boltzmann-Machine 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.

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Restricted-Boltzmann-Machine releases are not available. You will need to build from source code and install.

Restricted-Boltzmann-Machine has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Sample from the distribution
Sigmoid sampling
Performs sampling
Return the sigmoid function
R Compute the energy of a transition matrix
Perform the forward computation
Calculate the energy of the mesh
Train the model
Calculate the contrastive divergence between two points

Get all kandi verified functions for this library.

Restricted-Boltzmann-Machine Key Features

No Key Features are available at this moment for Restricted-Boltzmann-Machine.

Restricted-Boltzmann-Machine Examples and Code Snippets

No Code Snippets are available at this moment for Restricted-Boltzmann-Machine.

Community Discussions

Trending Discussions on Restricted-Boltzmann-Machine

What does the greater-than symbol mean in this piece of python code?

QUESTION

What does the greater-than symbol mean in this piece of python code?

Asked 2017-May-11 at 04:54

I am trying to implement a restricted boltzmann machine in C++. I am using this Python code as a guide: https://github.com/echen/restricted-boltzmann-machines/blob/master/rbm.py

This is Line 37:

...

ANSWER

Answered 2017-May-11 at 04:33

Due to operator overloading, the > operator can do practically anything -- it simply invokes the __gt__ special method on the object. But absent any other information, I would expect it to simply evaluate "greater than" and return a bool value.

Source https://stackoverflow.com/questions/43906539

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

Vulnerabilities

No vulnerabilities reported

Install Restricted-Boltzmann-Machine

You can download it from GitHub.
You can use Restricted-Boltzmann-Machine 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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