It's I/O season once again and this year it will be coming to you live from Google I/O Extended Toronto 2018 at Devhub!
Date: May 8th, 2018
Time: Doors open at 12:30pm, Keynote begins at 1:00pm, TensorFlow Study Jam Kicks Off at 5:30pm
Location: Devhub - 46 Spadina Ave, Suite 400, Toronto, ON.
Timetable (time and schedule subject to change):
12:30pm - Doors Open
1:00pm - 5:00pm - Keynote live streamed.
5:00pm - 5:30pm - Dinner (provided), Networking, and Workshop set-up
5:30pm - 8:30pm - TensorFlow Crash Course Kick off
On Tuesday, May 8th, come join us at Devhub for Google I/O Extended Toronto 2018!
We’ll be streaming the Google I/O Keynote beginning at 1:00pm and kick off our upcoming TensorFlow Study Jam at 5:30pm. If you have wanted to get started in doing Machine Learning with TensorFlow, feel free to join us and be a part of the exciting upcoming Study Jam Series!
I/O Extended is being co-hosted and held at Devhub. They have a beautiful co-working space which they are opening up for attendees. This means that while we stream the keynote and subsequent sessions you’ll be able to work there for the day. This will give you the chance to both participate in Google I/O Extended and not lose out on a day of work.
Specific details are subject to change, as we continue to work at bringing you an outstanding I/O Extended experience.
About the TensorFlow Study Jam Kick Off: Following the Google IO Live Stream, we invite participants to stick around for the kick-off of our Machine Learning with TensorFlow Crash Course series.
Over the next 8 weeks, we invite participants to join us as we follow along with the Course materials provided by Google:
During the kick-off, we will be going through a high level exploration of Machine Learning concepts, the technologies and tools involved, and going through some hands-on activities to help participants set targets for the 8-week series.
Even if the full Crash Course is too much of a commitment for you right now, this introductory session may still be of benefit if you have never had a chance to dig into what Machine Learning is all about.
Topics we will be covering during the session:
1. Machine Learning: beyond the buzzword
2. Understanding the problems that Machine Learning can and cannot solve
3. Where Machine Learning fits in our current world
4. Identifying a Machine Learning Problem
5. Technologies involved to get up and running with Machine Learning
- which programming languages do I need to know and why?
- how much Math do I really need to know?!
- how powerful of a Computer do I need access to?
6. Sources of data for Machine Learning activities
At the end of this session, participants will have:
- identified a Machine Learning problem to solve
- identified possible sources of data to solve their problem
- articulated potential success targets for their Machine Learning algorithm
We will also be taking a look at materials to review in advance of Machine Learning Crash Course session #2 (homework!!!!).
In upcoming weeks, we will be following along with the Machine Learning Crash Course on Wednesday evenings from 6:30 - 8:30pm through the end of June.
Look forward to seeing you there!
-The GDG Toronto Team and the folks at Devhub
Note: Unfortunately, the space at 46 Spadina Ave, Suite 400 is not wheelchair accessible. If you require any other accommodations, please reach out to us, and we’ll do what we can to help.