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About the developer

hunkim
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Description

TensorFlow Basic Tutorial Labs

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Contributors list

Lab code (WIP), but call for comments

Build Status

This is code for labs covered in TensorFlow basic tutorials (in Korean) at https://youtu.be/BS6O0zOGX4E. (We also have a plan to record videos in English.)

This is work in progress, and may have bugs. However, we call for your comments and pull requests. Check out our style guide line:

  • More TF (1.0) style: use more recent and decent TF APIs.
  • More Pythonic: fully leverage the power of python
  • Readability (over efficiency): Since it's for instruction purposes, we prefer readability over others.
  • Understandability (over everything): Understanding TF key concepts is the main goal of this code.
  • KISS: Keep It Simple Stupid! https://www.techopedia.com/definition/20262/keep-it-simple-stupid-principle-kiss-principle

Lab slides:

  • https://goo.gl/jPtWNt

We welcome your comments on slides.

File naming rule:

  • klab-XX-X-[name].py: Keras labs code
  • lab-XX-X-[name].py: TensorFlow lab code
  • mxlab-XX-X-[name].py: MXNet lab code

Install requirements

pip install -r requirements.txt

Run test and autopep8

TODO: Need to add more test cases

python -m unittest discover -s tests;

http://stackoverflow.com/questions/14328406/

pip install autopep8 # if you haven't install autopep8 . --recursive --in-place --pep8-passes 2000 --verbose

Automatically create requirements.txt

pip install pipreqs

pipreqs /path/to/project

http://stackoverflow.com/questions/31684375

Contributions/Comments

We always welcome your comments and pull requests.

Reference Implementations

  • https://github.com/nlintz/TensorFlow-Tutorials/
  • https://github.com/golbin/TensorFlow-ML-Exercises
  • https://github.com/FuZer/Study_TensorFlow
  • https://github.com/fchollet/keras/tree/master/examples

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