# DeepLearningZeroToAll

**Repository Path**: zhb186/DeepLearningZeroToAll

## Basic Information

- **Project Name**: DeepLearningZeroToAll
- **Description**: TensorFlow Basic Tutorial Labs
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-11-16
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Lab code (WIP), but call for comments

[![Build Status](https://travis-ci.org/hunkim/DeepLearningZeroToAll.svg?branch=master)](https://travis-ci.org/hunkim/DeepLearningZeroToAll)

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
```bash
pip install -r requirements.txt
```

## Run test and autopep8
TODO: Need to add more test cases

```bash
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

```bash
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