stanford-tensorflow-tutorials | repository contains code examples for the Stanford | Machine Learning library

by chiphuyen Python Version: v2.0.0 License: MIT

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kandi X-RAY | stanford-tensorflow-tutorials Summary

stanford-tensorflow-tutorials is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. stanford-tensorflow-tutorials has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However stanford-tensorflow-tutorials build file is not available. You can download it from GitHub.

This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

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stanford-tensorflow-tutorials has a medium active ecosystem.

It has 10253 star(s) with 4380 fork(s). There are 634 watchers for this library.

It had no major release in the last 12 months.

There are 67 open issues and 41 have been closed. On average issues are closed in 90 days. There are 20 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of stanford-tensorflow-tutorials is v2.0.0

Quality

stanford-tensorflow-tutorials has 0 bugs and 0 code smells.

Security

stanford-tensorflow-tutorials has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

stanford-tensorflow-tutorials code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

stanford-tensorflow-tutorials 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

stanford-tensorflow-tutorials releases are available to install and integrate.

stanford-tensorflow-tutorials has no build file. You will be need to create the build yourself to build the component from source.

stanford-tensorflow-tutorials saves you 2207 person hours of effort in developing the same functionality from scratch.

It has 4831 lines of code, 346 functions and 82 files.

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

Top functions reviewed by kandi - BETA

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

Create a chat bot
Construct a response based on input logits
Get user input
Find the right bucket with the given length
Train the model
Saves an image
Loads a VGG network
Calculate the average pool
Generate embeddings
Return the most common words in the vocabulary
Read a MNIST dataset
Calculate neural GPU with the given parameters
Generate a word2vec
Create summaries for the model
Get a resized image
Read a tfrecord image
Normalize an image
Generator for batch of data
Convolutional layer
Loads the convolutional network
Performs training
Create the content loss for the given image
Download the pretrained model
Download the MNIST dataset
Read birthlife data from file
Download the given file

Get all kandi verified functions for this library.

stanford-tensorflow-tutorials Key Features

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stanford-tensorflow-tutorials Examples and Code Snippets

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Community Discussions

Trending Discussions on stanford-tensorflow-tutorials

Unable to clone repository while connected to VPN. SSL: certificate subject name does not match target host name 'github.com'

QUESTION

Unable to clone repository while connected to VPN. SSL: certificate subject name does not match target host name 'github.com'

Asked 2020-Apr-12 at 13:44

I am trying to clone a git repository on a remote system connected via ssh. I need to connect to the VPN in order to ssh to the local machine of my organization.

I am trying to clone this git repository but I am getting SSL error,

...

ANSWER

Answered 2020-Apr-12 at 13:44

You can disable certificate verification;

Source https://stackoverflow.com/questions/61170411

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

Vulnerabilities

No vulnerabilities reported

Install stanford-tensorflow-tutorials

You can download it from GitHub.
You can use stanford-tensorflow-tutorials 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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