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

[EricPB (Eric Perbos-Brinck)]

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:
http://www.fast.ai/2017/09/08/introducing-pytorch-for-fastai/

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 ?
http://www.fast.ai/2017/07/17/num-lin-alg/

Best regards,

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

Part 1: complete collection of video timelines

As a companion to the post “Part #2: complete collection of video timelines”, please find his twin brother for Part #1 below. Note: this post is an ensemble of the video timelines created by interns & students of Part #1 in the Wiki; I made some editing to keep the flow consistent between lessons. The full Part #2 video syllabus is available here: Lesson 1 video timeline 00:00:00 - Fast AI & the course https://youtu.be/Th_ckFbc6bI?t=1s 00:05:29 - Why Deep Learning is exciting https:…

[gnak]

Hejsan,

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?