Giter Site home page Giter Site logo

hands-on-ai-tools's Introduction

AI 工具手把手工作坊 Hands-on-AI-Tools

簡介

會使用到的 Python 函式庫有:

  1. NumPy:矩陣運算函式庫
  2. Scikit-learn:機器學習函式庫
  3. Pandas:資料處理函式庫
  4. Jieba:中文斷詞函式庫
  5. Jupyter Notebook:編譯器環境

學生需要預先安裝好 Python 2.7 的環境,安裝教學請見「安裝簡易教學」,建議非資訊科背景同學請資訊科同學在一旁協助。(請注意:由於每個人的電腦開發環境不同,安裝簡易教學並非適用於每個人的電腦,若遇到安裝問題,請善用 Google 查詢錯誤關鍵字尋求答案)

安裝簡易教學

Mac OS X

Step1 安裝

Installing Python on Mac OS X(使用 homebrew):https://pythonguidecn.readthedocs.io/zh/latest/starting/install/osx.html

Step2 Virtualenv 安裝與使用

打開終端機(Terminal),輸入:

pip install virtualenv

創建虛擬環境:

virtualenv ENV

啟動虛擬環境:

source ENV/bin/activate

Step3 下載教學範例環境

下載程式碼,使用 git clone 指令(或是下載壓縮檔也可以):

git clone https://github.com/fukuball/Hands-on-AI-Tools.git

進入教學範例資料夾:

cd Hands-on-AI-Tools

安裝相關套件:

pip install -r requirements.txt

Step4 確認安裝完成,開啟 Jupyter Notebook

確認安裝完成,開啟 Jupyter Notebook:

jupyter notebook

Jupyter Notebook 會開啟一個伺服器,通常網址是:http://localhost:8888,在瀏覽器輸入網址就可以看到筆記本了,到這邊應該就完成課程開發環境的安裝了~

Windows

Step1 安裝

Installing Python on Windows:https://pythonguidecn.readthedocs.io/zh/latest/starting/install/win.html

Step2 Virtualenv 安裝與使用

打開命令提示字元(CMD),輸入:

pip install virtualenv

創建虛擬環境:

virtualenv ENV

啟動虛擬環境:

ENV\Scripts\activate

Step3 下載教學範例環境

下載程式碼,解壓縮後,進入教學範例資料夾:

cd Hands-on-AI-Tools

安裝相關套件:

pip install -r requirements.txt

Step4 確認安裝完成,開啟 Jupyter Notebook

確認安裝完成,開啟 Jupyter Notebook:

jupyter notebook

Jupyter Notebook 會開啟一個伺服器,通常網址是:http://localhost:8888,在瀏覽器輸入網址就可以看到筆記本了,到這邊應該就完成課程開發環境的安裝了~

監督式學習

分類學習

  1. 惡性腫瘤分類問題(二元分類):使用 Logistic Regression Classifier、Stochastic Gradient Descent Classifier
  2. 手寫數字分類問題(多元分類):使用 Support Vector Machine Classifier

回歸預測

  1. 美國波士頓房價問題:使用 Linear Regression、Stochastic Gradient Descent Regression

  2. 美國波士頓房價問題:使用 Support Vector Machine Regression、Cross Validation 的技巧

非監督式學習

  1. K-Means 分群,如何應用在手寫數字分類問題上

自然語言處理

  1. Jieba 中文斷詞工具使用
  2. 使用 LSA 潛在語意分析

hands-on-ai-tools's People

Contributors

fukuball avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.