deep_learning_nlp | deep learning for nlp | Machine Learning library

by tigerneil Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | deep_learning_nlp Summary

deep_learning_nlp is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. deep_learning_nlp has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

deep learning for nlp.

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Quality

Security

License

Reuse

Support

deep_learning_nlp has a low active ecosystem.

It has 4 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

deep_learning_nlp has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of deep_learning_nlp is current.

Quality

deep_learning_nlp has no bugs reported.

Security

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

License

deep_learning_nlp 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

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

Decorator to collect the phase of a function
Insert new node before node
Clone the node
Return whether the document has content
Build an Element Builder
Converts the given XML name into the name
Returns True if the version matches the given version
Serialize an element
Return the platform name
Get configuration variables
Uninstall this requirement
Parse CLI arguments
Finalize options
Run pip
Get global configuration variables
Install the wheel
Returns a list of supported binaries
Find all plugins in the environment
Update the version
Build the distribution
Send a request
Parse makefile
Find a distribution
Prepare a requirement
Return a DOM builder
Install the distribution
Run command

Get all kandi verified functions for this library.

deep_learning_nlp Key Features

No Key Features are available at this moment for deep_learning_nlp.

deep_learning_nlp Examples and Code Snippets

No Code Snippets are available at this moment for deep_learning_nlp.

Community Discussions

Trending Discussions on deep_learning_nlp

Browser-friendly way of drawing rectangles on top of image R Shiny

QUESTION

Browser-friendly way of drawing rectangles on top of image R Shiny

Asked 2020-Jan-21 at 17:37

I have written a shiny app that allows the user to draw rectangles on top of an image (minimal reproducible example below).

The problem with my current approach is that every time a rectangle is added, a new image is created, written to disk, and rendered (sent to the user's browser). This takes quite some time, and becomes really annoying when the Internet connection is slow.

Is there any way to display the rectangles on top of the image directly in the browser, without modifying the image on the server side? The only thing I need to ensure is that the browser sends back to the server the rectangles coordinates over the plot.

A good example of what I'm looking for (in JavaScript): https://kyamagu.github.io/bbox-annotator/demo.html I know JavaScript can be embedded in a Shiny app through a widget, if no one proposes an easier solution, that's what I'll do.

...

ANSWER

Answered 2020-Jan-21 at 17:37

Here's a JS option based entirely on this answer.

Source https://stackoverflow.com/questions/59718113

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

Vulnerabilities

No vulnerabilities reported

Install deep_learning_nlp

You can download it from GitHub.
You can use deep_learning_nlp 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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