From Ng’s machine learning to deep learning

Mainly record the differences in symbols and descriptions between the two courses in the learning process

Linear regression sign change

X0 becomes B, theta becomes W

In ML, I’m going to add a row x0 to the first row of my X matrix

y = X * theta.T
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In DL, it’s b alone

y = w.T * X + b
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Default row vectors become column vectors

So, the linear regression computation time becomes as follows

y = w.T * X + b
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That’s the same thing as when X is a row vector

y = X * w.T + b
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