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Hey Data Explorers,

Thanks to the generous offer by folks at Sidewalk Labs, we are able to discuss lecture 1 in their amazing space! Please note that this is an ADDITIONAL session to Thursday this week. The conference room is good for only 10 people sitting by the table, so please come early if you want to use the table. We can still add a few more chairs in the back but please respect the limit and UPDATE your RSVP if you cannot make it.

What to expect in this session:

  1. Get to know each other
  2. Finish watching lecture 1 if you haven't
  3. Set up your deep learning environment
  4. Go through notebooks 1 and 2 and complete training your first CNN image classifier

What's required to attend this session:

  1. an account on https://forums.fast.ai
  2. intermediate Python (the course website says 1 year of coding. Basically the more coding experience you have the faster you will learn, but it's recommended that you know all the basics in an intro to Python course, or there will be lots of catching up to do!)
  3. high school math
  4. a laptop
  5. completed watching lecture 1 (or you'll spend time watching it during the session)
  6. be friendly :)

General Series Format:
There are at least 2 sessions (Mondays and Thursdays) per week for 7 weeks (Oct 29 - Dec 13). Currently the setup is the following:

Mondays: Watching the lectures together (~ 2hrs)
Thursdays: Discussion lead by Xu Fei and then coding, as well as for those who want to catch up with the Monday lecture.

Xu Fei went to USF earlier this year and completed the Fastai part 2 Cutting Edge Deep Learning for Coders in person. This time he'll share as many things that helped him in the course as possible, and hope to learn from everyone else.

Since this is a pretty intense course, we can also add a few sessions on weekends (location TBD) for those who need additional help, or whoever wants to work on solving problems together. This will be determined by everyone before the end of Thursday.

Cost:
Your time

Why is this course offered for free?
We offer it for free because the creators of the course keep it that way for the online version. Please read more in the "Additional Info" section below for the mission of Fastai, and you will find out more once you join the course ;)

Additional Info:
This course is the 3rd run of Practical Deep Learning For Coders, Part 1 offered by Fast.ai. It uses the brand new Fastai v1 library, based on PyTorch 1.0 released at the beginning of October 2018. You can think of Fastai to PyTorch as Keras to TensorFlow, or take a quick look at this quote
https://twitter.com/jeremyphoward/status/1047215781023367168

If you haven't heard of the Fastai deep learning course, please take a look at their previous courses:
http://course.fast.ai/start.html

An inspiring TEDxSF talk by Rachel Thomas why she and Jeremy Howard started Fastai:
https://www.youtube.com/watch?v=LqjP7O9SxOM

A very recent article covering Fastai in The Economist.
https://www.economist.com/business/2018/10/27/new-schemes-teach-the-masses-to-build-ai?frsc=dg%7Ce

Currently the course is taking place at University of San Francisco every Monday evening (started on October 22nd for 7 weeks). Although the deadline to register for the live online version has passed, we fortunately got permission from the instructor Jeremy Howard to share the latest course content with our group members offline, so motivated learners from Toronto can access the raw/live version almost in sync (with 1 week of delay) with the San Francisco students. The polished version will be open to the public in January 2019.

Events in Toronto, ON

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