/workshop_blog

Primary LanguageJupyter NotebookMIT LicenseMIT

Firstly, please open this README document using your own web browser: https://github.com/telescopeuser/workshop_blog

配套视频教程的链接:

YouTube

优酷 [To be announced]

[零基础系列教程] 如何开发微信聊天机器人并集成深度人工智能应用

Workshop series: How to embed advanced machine intelligence into a chatbot for social media App WeChat, using Google cloud and machine learning APIs

WeChat is a popular social media app, which has more than 800 million monthly active users.

http://www.KudosData.com

by: Sam Gu [ Data Science Trainer @ 酷豆数据科学 ]

April 2017 ====== Scan the QR code to add me in WeChat ====>>

Acknowledgement

1. 教程大纲 Workshop Content

第一课：微信问答机制使用基础

Lesson 1: Basic usage of WeChat Python API

  • 使用和开发微信个人号聊天机器人：一种Python编程接口 (Use WeChat Python API)
  • 用微信App "扫一扫" QR码图片来自动登录 (Log-in WeChat account)
  • 查找指定联系人或群聊 (Scan contact list)
  • 发送信息（文字、图片、文件、音频、视频等） (Send message: text, image, file, voice, video, etc)
  • 接收信息 (Receive message, and keep 'listening')
  • 自动回复 (Receive message and then automaticaly reply)
  • 自定义复杂消息处理，例如：信息存档、回复群聊中被@的消息 (Advanced message processing and reply)

第二课：图像识别和处理

Lesson 2: Image Recognition & Processing

  • 识别图片消息中的物体名字 (Recognize objects in image) [1] 物体名 (General Object) [2] 地标名 (Landmark Object) [3] 商标名 (Logo Object)

  • 识别图片消息中的文字 (OCR: Extract text from image) 包含简单文本翻译 (Call text translation API)

  • 识别人脸 (Recognize human face) 基于人脸的表情来识别喜怒哀乐等情绪 (Identify sentiment and emotion from human face)

  • 不良内容识别 (Explicit Content Detection)

第三课：自然语言处理：语音合成和识别

Lesson 3: Natural Language Processing 1

  • 消息文字转成语音 (Speech synthesis: text to voice)
  • 语音转换成消息文字 (Speech recognition: voice to text)
  • 消息文字的多语言互译 (Text based language translation)

第四课：自然语言处理：语义和情感分析

Lesson 4: Natural Language Processing 2

  • 消息文字中名称实体的识别 (Name-Entity detection)
  • 消息文字中语句的情感分析 (Sentiment analysis, Sentence level)
  • 整篇消息文字的情感分析 (Sentiment analysis, Document level)
  • 语句的语法分析 (Syntax / Grammar analysis)

第五课：视频识别和处理

Lesson 5: Video Recognition & Processing

  • 识别视频的场景片段 (Detect shots change in video)
  • 识别视频消息中的物体名字 (Recognize objects in video/shots)
  • 直接搜索视频内容 (Search content in video)

第六课：互动智能机器人应用

Lesson 6: Intelligent & Interactive Chat-bot Applications

  • 多语言翻译器 (Language translator)
  • 图文多媒体的订阅和点播 (Multi-media broadcast & on-demand subscription)
  • 文章的概括和缩写 (Automatic article summary)
  • 不良图片的识别；不良视频片段的自动识别和定位 (Explicit content detector: i.e. adult content or violent content)
  • 基于商品图片的搜索和商家价格比较 (Best retail price finder using an image of goods)

2. 开发环境安装

选择1：下载使用酷豆虚拟机

Option 1: Use a Virtual Machine to run in your own computer (Difficulty level: Easy, like being a boss)

选择2：使用云平台

Option 2: Use Cloud Platform (Difficulty level: Medium, as bribing your colleague)

Create an account in Google Cloud Platform (GCP)

Start Datalab (Jupyter python notebook) using Cloud Shell

  • Create/Connect a GCP Compute Engine virtual machine to use Datalab: kudosdata01-vm-datalab-workshop <--- In case you are lost here, quick guide: https://cloud.google.com/datalab/docs/quickstarts

    gcloud projects list

    gcloud config set core/project kudosdata01 [your own unique project-id]

    gcloud config set compute/zone asia-east1-b

    datalab create kudosdata01-vm-datalab-workshop --zone asia-east1-b [1st time for creation]

    datalab connect kudosdata01-vm-datalab-workshop [2nd time for connection]

    datalab stop kudosdata01-vm-datalab-workshop [stop VM after use]

  • Open Datalab in web browser, then create a new notebook from datalab folder, then run below two command in notebook cell:

    !git clone https://github.com/telescopeuser/workshop_blog.git

    %load workshop_blog/setup_cloud.py

选择3：本地电脑安装

Option 3: Use your own computer (Difficulty level: High, as what you normally do)

3. 恭喜您！安装成功了！下一步进入具体课程和实战操作，请打开第一课的笔记本。 Congratulations! After completing one of the installation options, you are now ready to rock! Go to GCP Datalab folder: workshop_blog/wechat_tool, open Notebook and follow...