feature scaling:缩小或扩大feature的值，使所有的feature处于类似的范围，这样进行gradient descnet时更快趋向最小值.因为不同的feature的范围相差很大时，它的cost function的等值线是椭圆的，但当它们相近时，等值线接近于圆，这样趋向最小值是，圆更快，椭圆更曲折，趋向更慢。(一般在+3到-3的范围内即可)

mean normalization:

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