Differences between "DL Part 1" from 2016 and 2017 incoming?

Hi @jeremy & @rachel !

I’m super excited to join the incoming “Deep Learning Part 1” 2017 edition starting on Oct 30th.

Apart from the switch from Keras/Theano/Py27 to Pytorch/Py36 as documented here:

How different will the content be vs the 2016 shown in the Wiki ?

Also is completing most/parts of Rachel’s course “Computational Linear Algebra” before a pre-req ?

Best regards,

PS: for those looking for a detailed syllabus of “Part 1 2016”, here’s a collection of video timelines.


I’m also excited to do the course starting 30th of October.

I am looking to work on something that can be good preparation for the course until it starts. I have the Coursera course machine learning under my belt. I’m thinking of working through Convolutional Neural Networks for Visual Recognition http://cs231n.stanford.edu/.

Do anyone have any thoughts or suggestions on good preparation for the Part 1?