機器學習百日馬拉松

這次參加這個第二屆機器學習百日馬拉松的活動，算是給自己一個動力去好好把與資料處理相關的基礎打穩。裡面主要是採用python，配合numpy與pandas這兩個套件處理資料。 Github這邊主要我就是放上每日的作業，詳細的心得之後會再整理。

先備知識

關於機器學習的大概念：Google Machine Learning Crash Course

（這個課程我覺得超棒！出現的觀念都講解的很仔細，也有提供更深入的資料可以閱讀以及實際的數據可以操作，大概十個多小時就可以全部看完。）

Numpy套件：從零開始學資料科學：Numpy 基礎入門

（Numpy是個可以平行處理多維度矩陣的套件，廣泛地被應用於資料科學的領域之中，這次使用的Pandas也是建立在Numpy的基礎上。）

Pandas套件：從pandas開始Python與資料科學之旅

（很詳細的說明，看完就可以開始實作了！Pandas不僅可以處理資料的載入、整理及操作，也可以進行資料視覺化的呈現。）

每日作業

（使用的是運行在Jupyter notebook上的.ipynb檔。）

一、資料清理數據前處裡

第一部分的心得：機器學習馬拉松（一） — EDA、標準化、相關係數、KDE、離散化

二、資料科學特徵工程技術
三、機器學習基礎模型建立

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Day_058_hierarchical_clustering_HW.ipynb		Day_058_hierarchical_clustering_HW.ipynb
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Day_060_PCA_HW.ipynb		Day_060_PCA_HW.ipynb
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Day_067_Keras_Dataset_HW.ipynb		Day_067_Keras_Dataset_HW.ipynb
Day_068_Keras_Sequential_Model_HW.ipynb		Day_068_Keras_Sequential_Model_HW.ipynb
Midterm.ipynb		Midterm.ipynb
README.md		README.md

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機器學習百日馬拉松

先備知識

關於機器學習的大概念：Google Machine Learning Crash Course

Numpy套件：從零開始學資料科學：Numpy 基礎入門

Pandas套件：從pandas開始Python與資料科學之旅

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機器學習 百日馬拉松

先備知識

關於機器學習的大概念：Google Machine Learning Crash Course

Numpy套件：從零開始學資料科學：Numpy 基礎入門

Pandas套件：從pandas開始Python與資料科學之旅

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機器學習百日馬拉松

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