Now for weak learners - https://drive.google.com/open?id=1aHaV0Whfq7W9VP0b1QAvDsEDq-TmM9E3

Continuing with features engineering.   Going to present orthogonal matching - https://drive.google.com/open?id=1UNykdybhGXuZ0ZDYBURYTyNB4H4HoXhF

We'll speak of automatic feature selection in the NL and group representation. - https://drive.google.com/open?id=1J4nYEYn7cIReLcO4RQGFgFxAqHIXQFc1

Now for the connection between convex optimization and learning.   https://drive.google.com/open?id=1rL5uUOrJAY9vvH5h4KZTxWeTGToaAf6M

We'll revisit k-means clustering today in the context of convexity - https://drive.google.com/open?id=0BzUXUMab8u_ZRFFMNmExeno3bWc

Convex optimization at https://drive.google.com/open?id=1ww3EdNS0IZi5S2ZQXVg9qkIjqa532_YM and data pipe line discussion. 

Still convex optimization - https://drive.google.com/open?id=1mGctnLSTAVGk_a-0R1g4t6ysFczYpcpH