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### 實用資源整理 :bread: 

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#### [學習資源] [資料集來源] [技術更新] 
#### [Paper With Code](https://paperswithcode.com/)

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#### [實用工具] 
#### [Git](https://git-scm.com/)
#### [Github](https://github.com/)

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#### [實用工具] 
#### Python Notebook - Colab & Jupyter Notebook
#### [Colab](https://colab.research.google.com/notebooks/intro.ipynb)
#### [Jupyter Notebook](https://jupyter.org/)

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#### [資料集來源(?)] [學習資源] [應用實戰]
#### [Kaggle Datasets](https://www.kaggle.com/datasets)
#### [Kaggle Courses](https://www.kaggle.com/learn)
#### [Kaggle Competitions](https://www.kaggle.com/competitions)

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#### [學習資源] 
#### [Hung-yi Lee](https://www.youtube.com/channel/UC2ggjtuuWvxrHHHiaDH1dlQ)
{%youtube c9TwBeWAj_U %}

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#### [學習資源] [靈感來源(?)] 
#### [Medium](https://medium.com/)

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#### [資料集來源]
#### [政府資料開放平台](https://data.gov.tw/)

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#### [應用範例-視覺化工具] 
#### [Plotly](https://plotly.com/python/)

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#### [學習資源] 
#### [Coursera](https://zh-tw.coursera.org/courses?query=free)

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#### [學習資源] 
#### [資料科學・機器・人](https://brohrer.mcknote.com/zh-Hant/)

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#### [學習資源] Data Science or Machine Learning? 
###### 聽聽大神怎麼說↓ *(06:17-10:54)*  :leaves: [Lee Meng's Blog](https://leemeng.tw/)
{%youtube sCkn1PQciws%}

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