TensorFlow and Deep Learning : TensorFlow 2.0 Introduction and Guide


Due to room availability, we will start a little later than usual at 7:30pm

The focus for this MeetUp's main talks will be on looking towards the future of TensorFlow, but we'll also include Deep Learning content to make sure there's something for everyone.

Planned Talks :

TensorFlow 2.0 is coming. We will give you a glimpse of the planned changes, and describe our plans to make the transition as painless as possible. Also, we will give you an overview of the many alternative platforms your TensorFlow can train and run on, including Swift, JavaScript and mobile devices.

Speaker Bio: Frank Chen is a Software Engineer at Google Brain, working to help make TensorFlow and TPUs faster and easier to use for everyone. Before Google, he worked on online education platforms as one of the founding software engineers at Coursera. When not working, Frank enjoys photography and musical theater and has seen over 30 Broadway shows. Frank has Bachelor's and Master's degrees in Computer Science from Stanford.

"Raw Audio to Piano Transcription" - Martin Andrews
Google's Magenta team has created a network to convert raw audio files to a midi piano roll, and has now released the python backend, a Colab notebook and an in-browser (local Javascript) version. Martin will describe how their Deep Learning network is built, the special 'losses' required to make it perform so well, and demonstrate it in action on music sourced 'in the wild'.

"Let Google do the pretraining for you: Exploring TF Hub" - Sam Witteveen
Introduced earlier this year TF Hub provides pretrained components and parts of graphs that you can implement into your models very quickly and easily. Sam will walk through some use cases and show code for using TF Hub modules in your own projects.


Talks will start at 7:30pm (A/V equipment permitting) and end at around 9:00pm, at which point people normally come up to the front for a bit of a chat with each other, and the speakers.


As always, we're actively looking for more speakers for future events - both '30 minutes long-form', and lightning talks. For the lightning talks, we welcome folks to come and talk about something cool they've done with TensorFlow and/or Deep Learning for 5-10mins (so, if you have slides, then #max=10). We believe that the key ingredient for the success of a Lightning Talk is simply the cool/interesting factor. It doesn't matter whether you're an expert or and enthusiastic beginner: Given the responses we have had, we're sure there are lots of people who would be interested to hear what you've been playing with. Please suggest yourself here :