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Update README.md
DEVHARAM May 5, 2018
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Update README.md
DEVHARAM May 27, 2018
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Create README_kr.md
DEVHARAM May 27, 2018
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12 changes: 8 additions & 4 deletions README.md
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### In English

# How_to_use_Tensorflow_for_classification-LIVE
This is the code for the "How to Use Tensorflow for Classification" live session by Siraj Raval on Youtube

##Overview
## Overview

This is the code for [this](https://www.youtube.com/watch?v=4urPuRoT1sE) live session by Siraj Raval on Youtube. We'll build
a classifier for houses. The housing data contains features for each house like # of bathrooms, price, and area. We'll manually add labels to our data (good buy or bad buy) then given a new house, we'll predict whether or not it's a good buy or bad buy. We use gradient descent as our optimization strategy and

##Dependencies
## Dependencies

* matplotlib
* [tensorflow](https://www.tensorflow.org/get_started/os_setup)
Expand All @@ -16,10 +18,12 @@ a classifier for houses. The housing data contains features for each house like
Install dependencies using [pip](https://pip.pypa.io/en/stable/)
Install jupyter notebook using [this](http://jupyter.readthedocs.io/en/latest/install.html)

##Usage
## Usage

type `juptyer notebook` into terminal and a browser window will pop up. Click on demo.ipynb. You can iteratively compile
each block of code to see the output results.

##Credits
## Credits
Credits for the code go to [jalammar](https://github.com/jalammar). I've merely created a wrapper to get people started.


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# 분류를 위해 Tensorflow를 사용하는 방법-LIVE
이것은 "분류를 위해 Tensorflow를 사용하는 방법"에 대한 코드입니다. Siraj Raval의 Youtube 라이브 세션

## 개요

이것은 [this](https://www.youtube.com/watch?v=4urPuRoT1sE) 라이브 세션에서 YouTube의 Siraj Raval의 코드입니다. 우리는 주택에 대한 분류기를 구축 할 것입니다. 주택 데이터는 욕실 수, 가격 및 면적과 같은 각 집의 기능을 포함합니다. Google은 데이터에 수작업으로 라벨을 추가 (좋은 구매 또는 나쁜 구매) 한 다음 새 집을 부여하여 좋은 구매인지 나쁜 구매인지 예측합니다. 그라디언트 디센트를 최적화 전략으로 사용하고

## 종속성

* matplotlib
* [tensorflow](https://www.tensorflow.org/get_started/os_setup)
* 팬더
* numpy

[pip](https://pip.pypa.io/en/stable/)를 사용하여 종속성 설치
[this](http://jupyter.readthedocs.io/en/latest/install.html)을 사용하여 jupyter notebook을 설치하십시오.

## 사용법

`juptyer notebook '을 터미널에 입력하면 브라우저 창이 열립니다. demo.ipynb를 클릭하십시오. 각 코드 블록을 반복적으로 컴파일하여 출력 결과를 볼 수 있습니다.

## 크레딧
코드에 대한 크레딧은 [jalammar](https://github.com/jalammar)로 이동하십시오. 나는 사람들을 시작할 수있는 래퍼를 만들었을뿐입니다.