NeuralPy | NeuralPy : A Keras like deep learning library works on top | Machine Learning library

by imdeepmind Python Version: v0.2.1 License: MIT

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

kandi X-RAY | NeuralPy Summary

NeuralPy is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Keras applications. NeuralPy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install NeuralPy' or download it from GitHub, PyPI.

NeuralPy is a High-Level Keras like deep learning library that works on top of PyTorch written in pure Python. NeuralPy can be used to develop state-of-the-art deep learning models in a few lines of code. It provides a Keras like simple yet powerful interface to build and train models. Here are some highlights of NeuralPy.

Support

Quality

Security

License

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Support

NeuralPy has a low active ecosystem.

It has 79 star(s) with 9 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 22 have been closed. On average issues are closed in 38 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of NeuralPy is v0.2.1

Quality

NeuralPy has 0 bugs and 0 code smells.

Security

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

NeuralPy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NeuralPy 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

NeuralPy releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

NeuralPy saves you 559 person hours of effort in developing the same functionality from scratch.

It has 6032 lines of code, 310 functions and 109 files.

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

Top functions reviewed by kandi - BETA

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

Builds the model
Build a Sequential layer from a dictionary
Sets the model
Generate a unique name for a layer
Predicts the classes of the model
Predict the model
Adds a layer to the model
Returns the PyTorch model

Get all kandi verified functions for this library.

NeuralPy Key Features

No Key Features are available at this moment for NeuralPy.

NeuralPy Examples and Code Snippets

No Code Snippets are available at this moment for NeuralPy.

Community Discussions

Trending Discussions on NeuralPy

Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-xaum7z8f/supervisor/

QUESTION

Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-xaum7z8f/supervisor/

Asked 2020-Apr-06 at 22:49

I'm setting up an existing project and when I am running pip install -r requirements.txt

After every dependency is installed it gives this error: Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-d0j9czw9/supervisor/

This is the list of complete installation

...

ANSWER

Answered 2020-Apr-06 at 22:25

The error is right at the end:

Source https://stackoverflow.com/questions/61069530

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

Vulnerabilities

No vulnerabilities reported

Install NeuralPy

To install NeuralPy, open terminal window type the following command:. If you have multiple versions of it, then you might need to use pip3. NeuralPy requires Pytorch and Numpy, first install those. Check the documentation for Installation related information.
Let's create a linear regression model in 100 seconds.