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2019 iT 邦幫忙鐵人賽

DAY 3
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機器學習與數學天天玩系列 第 3

Day 3-機器學習與數學天天玩-PCA-Statistical Introduction: Mean Value

Today is Staturday and I will continue my study on Coursera course with a simple summary.

Like what I shared yesterday, the brief structure leading to the milestone of PCA is as below:
1. Statistical Introduction
2. Transformation of Vectors in Spaces
3. Orthogonal Projection

In the statistical introduction, the course firstly introduces the meaning of mean value in a dataset D. The mean value is to have the summation of all elements in a dataset divided by the total number of elements.

https://ithelp.ithome.com.tw/upload/images/20181006/201115544wR6M0gEpc.png


Along with the course, a useful function marked as one of fundamental tools in develping PCA skill is: flatten()

x = np.matrix([[1, 2], [3, 4]])

Out[11]:
matrix([[1, 2],
[3, 4]])

x_reshaped = x.flatten()

Out[10]: matrix([[1, 2, 3, 4]])

By observing the above code, it is apparent that flatten() helps tranform values in a matrix from several layers into one row.


上一篇
Day 2-機器學習與數學天天玩-PCA
下一篇
Day 4-機器學習與數學天天玩-PCA-Statistical Introduction: Variance
系列文
機器學習與數學天天玩13

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