Lab code (WIP), but call for comments

This is code for labs covered in TensorFlow basic tutorials (in Korean) at https://www.youtube.com/watch?v=BS6O0zOGX4E&list=PLlMkM4tgfjnLSOjrEJN31gZATbcj_MpUm. (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.

dw-shin/DeepLearningZeroToAll