Mastering Machine Learning Algorithms: Errata Corrige and Additional Notes

In this page, you can find notes, errata corrige and additional pieces of information for the book “Mastering Machine Learning Algorithms“.

Gitter chatroom: https://gitter.im/Machine-Learning-Algorithms/Lobby

 

Page 32:

The formula at the end of the page is based on argmin, as this is a minimization:

 

Page 92:

The code snippet containing the loop for the label propagation is:

while np.linalg.norm(Yt - Y_prev, ord=1) > tolerance:
        P = np.dot(D_rbf_inv, W_rbf)
        Y_prev = Yt.copy()
        Yt = np.dot(P, Yt)
        Yt[0:nb_samples - nb_unlabeled] = Y[0:nb_samples - nb_unlabeled]

 

Mastering Machine Learning Algorithms – Giuseppe Bonaccorso

Today I’ve published my latest book ” Mastering Machine Learning Algorithms ” (in a few days it will be available on all channels). From the back cover: Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent.