pyquickhelper | publish materials for teaching , notebook rendering

by sdpython Jupyter Notebook Version: 1.12.3823 License: MIT

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

kandi X-RAY | pyquickhelper Summary

pyquickhelper is a Jupyter Notebook library. pyquickhelper has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Automation to publish materials for teaching, notebook rendering, sphinx extensions, Jenkins helpers...

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Quality

Security

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Support

pyquickhelper has a low active ecosystem.

It has 21 star(s) with 10 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 22 open issues and 300 have been closed. On average issues are closed in 140 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pyquickhelper is 1.12.3823

Quality

pyquickhelper has 0 bugs and 0 code smells.

Security

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

pyquickhelper code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pyquickhelper 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

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

It has 81381 lines of code, 3225 functions and 639 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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pyquickhelper Key Features

No Key Features are available at this moment for pyquickhelper.

pyquickhelper Examples and Code Snippets

No Code Snippets are available at this moment for pyquickhelper.

Community Discussions

Trending Discussions on pyquickhelper

Usage of LSTM/GRU and Flatten throws dimensional incompatibility error

QUESTION

Usage of LSTM/GRU and Flatten throws dimensional incompatibility error

Asked 2020-Sep-15 at 20:26

I want to make use of a promising NN I found at towardsdatascience for my case study.

The data shapes I have are:

...

ANSWER

Answered 2020-Aug-17 at 18:14

I cannot reproduce your error, check if the following code works for you:

Source https://stackoverflow.com/questions/63455257

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

Vulnerabilities

No vulnerabilities reported

Install pyquickhelper

You can download it from GitHub.

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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