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機器學習基礎教學

Home Page: https://github.com/AI-FREE-Team/Machine-Learning-Basic

License: MIT License

Jupyter Notebook 100.00%
machine-learning google-colab python-3 numpy pandas matplotlib scipy seaborn-plots scikit-learn

machine-learning-basic's Introduction

Machine Learning Basic

Python Numpy Pandas SciPy Matplotlib seaborn Scikit-Learn

image Welcome to the course 《Python: from business analytics to Artificial Intelligence》 by AI. FREE Team.
歡迎大家來到 AI. FREE Team 《Python 從商業分析到人工智慧》的第二堂課,機器學習(ML)基礎教學。

系列課程說明 Course Description

  • 《Pyhon 從商業分析到人工智慧》系列課程將透過 Google Colab 進行學習。(Google Colab是什麼?)
  • 本系列課程將免費提供給中文使用者學習資料科學,但不提供第三方做商業用途。(商業合作請洽AI . FREE Team)
  • 本系列課程將從基礎 Python的使用,到人工智慧的開發,讀者歡迎追蹤 粉絲專頁並加入 自由團隊-學習社團

課程大綱 Course Outline

⭐ 數據與特徵決定了機器學習的上限,而模型和演算法則只是在逼近上限。
⭐ Data and characteristics determine the upper limit of machine learning, and models and algorithms just approach this upper limit.

Topic 1: 認識基礎套件 Basic Packages
  • Colab
  • Colab
  • Colab
  • Colab

Topic 2: 介紹基礎的統計概念 Basic Statistics
  • Colab
  • Colab
  • Colab
  • Colab
  • Colab

Topic 3: 資料前處理 Data Pre-processing

Topic 4: 資料視覺化 Data Visualization
  • Colab
  • Colab
  • Colab
  • Colab
  • Colab


參考資源 References

使用指南 User Guide

[1] NumPy
[2] Pandas
[3] Matplotlib
[4] Scikit Learn

文章 Articles

[1] Introduction to Pandas apply, applymap and map, B. Chen, May 11, 2020.
[2] How to Use datetime.timedelta in Python With Examples, Miguel Brito, Nov 14, 2020.
[3] An Introduction to Discretization Techniques for Data Scientists, Rohan Gupta, Dec 7, 2019.
[4] Categorical encoding using Label-Encoding and One-Hot-Encoder, Dinesh Yadav, Dec 7, 2019.
[5] PCA — how to choose the number of components ?, Bartosz Mikulski, Jun 3, 2019.
[6] Mean Squared Error or R-Squared – Which one to use ?, Ajitesh Kumar, Sep 30, 2020.
[7] Splitting a Dataset into Train and Test Sets, A. Aylin Tokuç, Jan 14, 2021.

作者 Authors

- © Tom Wu (Github)
- © Michelle Chuang (Github)
- © Andy Chan (Github)

授權 License

Creative Commons License (CC BY-NC-SA 4.0)
本教學課程適用 Attribution-NonCommercial-ShareAlike 4.0 International 授權方式。

※ 轉載、改作、分享請附上以下內容:

  • 本課程由 AI . FREE Team 原創開發。如有轉載、改作、分享,請註明出處。
  • The course is AI . FREE Team original production. If reproduced, modified, or shared, please cite the source.
  • (source: https://github.com/AI-FREE-Team/Machine-Learning-Basic )

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