PRPN | Parsing Reading Predict Network | Machine Learning library

by yikangshen Python Version: Current License: MIT

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

kandi X-RAY | PRPN Summary

PRPN is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. PRPN has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However PRPN build file is not available. You can download it from GitHub.

Parsing Reading Predict Network

Support

Quality

Security

License

Reuse

Support

PRPN has a low active ecosystem.

It has 92 star(s) with 25 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 0 have been closed. On average issues are closed in 617 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of PRPN is current.

Quality

PRPN has no bugs reported.

Security

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

License

PRPN is licensed under the MIT License. This license is Permissive.

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

Reuse

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

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

Train the model
Splits the input data into batches
Repackage hidden variables
Calculate the loss criterion
Get a batch from source
Forward attention
Performs softmax attention
Softmax function
Tokenize a list of file ids
Adds a word to the vocabulary
Plot a numpy array
Creates a colour string
Splits data into batch sizes
Evaluate the model
Calculate the attention layer

Get all kandi verified functions for this library.

PRPN Key Features

No Key Features are available at this moment for PRPN.

PRPN Examples and Code Snippets

No Code Snippets are available at this moment for PRPN.

Community Discussions

Trending Discussions on PRPN

Bootstrapping in R: Predict

How can I get a true random from an array? Or should I do something else entirely?

QUESTION

Bootstrapping in R: Predict

Asked 2020-Mar-16 at 02:39

I am running a program where I conduct an OLS regression and then I subtract the coefficients from the actual observations to keep the residuals.

...

ANSWER

Answered 2020-Mar-16 at 02:39

If you're trying to fit the best OLS using bootstrap, I'd use the caret package.

Source https://stackoverflow.com/questions/60699413

QUESTION

How can I get a true random from an array? Or should I do something else entirely?

Asked 2019-Oct-02 at 16:01

I would like to display a different madlib each time a user clicks the submit button. Only needs to be clicked 3 times. I am using the functions below, but it doesn't seem all that random. I also have a snippet of the dogLib function that creates three madlibs and then calls the function above it to generate a random madlib string.

...

ANSWER

Answered 2019-Oct-02 at 15:21

So true randomness is going to be tough to achieve. Math.Random() from the javascript library isn't truly random as you've guessed, it's pseudo-random, meaning there is a pattern to it over a large number of inputs. Computers inherently can't really do true randomness, because they are always going to have to take some number, perform some sort of algorithm on it (these are usually "Mersenne Twisters" - fun wikipedia read), and spit out the result.

That said, I don't know exactly how to improve on what you've put into place here. With PRNG, a really large number of possible inputs can help a lot. If you want absolutely true randomness, the easiest way would probably be to hook into random.org's API (https://api.random.org/dashboard - developer license is free, limited to 1000 requests per day). Hooking into an API might be more work than you were planning on, but random.org uses (if I remember right) atmospheric noise and barometric pressure from the Earth to create their random numbers, so it's about as close to true randomness as you can possibly get.

I hope this helps!

Source https://stackoverflow.com/questions/58204055

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

Vulnerabilities

No vulnerabilities reported

Install PRPN

You can download it from GitHub.
You can use PRPN 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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