# How-to-do-sentiment-analysis-for-comments

This is a project for students in [LiveEdu](https://www.liveedu.tv/yingshaoxo/Z7vkO-ru-he-dui-ping-lun-jin-xing-wen-ben-qing-gan-fen-xi/) to keep in touch with the knowledge I taught.

### In the beginning

Hi! I'm your guide **yingshaoxo**. 

I'm here to help you guys to get into Machine learning as soon as possible.

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### 介绍

各位学子，你们好，我是你们的好朋友，**yingshaoxo**

我将通过这个课程为你们打开一扇新世界的大门: 一扇可以通过自学达到人类极限的大门。

### 目标

我们的最终目的是用`Python`构建一个可以检测文本(尤其是评论)的情感色彩的 `人工智能模型`

### 具体课程

**[Session 0](https://github.com/yingshaoxo/How-to-do-sentiment-analysis-for-comments/blob/master/0.ipynb):** 换个操作系统 (From Windows to Linux)

* Install Ubuntu
* Learn some basic Linux commands


**[Session 1](https://github.com/yingshaoxo/How-to-do-sentiment-analysis-for-comments/blob/master/1.ipynb):** 准备好环境 (Setting up the Machine Learning environment for Ubuntu)

* Install python3, python3-pip, git, jupyter
* Install scikit-learn, Tensorflow, Keras, GPU, ...


**[Session 2](https://github.com/yingshaoxo/How-to-do-sentiment-analysis-for-comments/blob/master/2.ipynb):** 初步理解机器学习 (Get some intuitions about Machine Learning by creating a linear regression model)

* Built your first scikit-learn model
* Convert scikit-learn model to Keras


**[Session 3](https://github.com/yingshaoxo/How-to-do-sentiment-analysis-for-comments/blob/master/3.ipynb):** 准备好数据 (Understand what is your need)

* The meaning of data
* Using selenium to grab data from websites
* Clear data with Python


**[Session 4](https://github.com/yingshaoxo/How-to-do-sentiment-analysis-for-comments/blob/master/4.ipynb):** 选择一个开源框架 (Trying to find an open source ML project to help us do the repeated work)

* Search wildly
* 选择一个合适的开源项目( 或教程
* 理解这个框架处理数据的大概流程


**[Session 5](https://github.com/yingshaoxo/How-to-do-sentiment-analysis-for-comments/blob/master/5.ipynb):** 训练模型 (Using Keras to do the dirty work)

* Train your AI model step by step


**Session 6:** 检测成果 (When we finished, we want to make sure that it works)

* Use model to do some predictions
