Introduction to deep learning

Speakers: Ricardo Pizarro, Arna Ghosh

Introduction to Deep Learning

Date: 2019-Feb-21

Time: 12:00 NOON

Venue: de Grandpré Communications Centre, Neuro, McGill

Thank you all for those who responded online and to those who were able to make it to our first meeting!

The responses we received online indicated that a large majority of the group have some informal background in the area of deep learning so we kick-started the series with a brief overview of machine and deep learning with a focus on popular classes of deep neural networks: convolution neural network (CNN) and recurrent neural network (RNN). Our aim of the first meeting was to ensure that all of us are roughly on the same page with respect to the terms popularly used in deep learning literature.

We introduced deep learning in broad strokes to help our discussions in subsequent meetings; however, for a more complete technical description of deep learning you would need to follow 1-2 semester long courses taught at McGill University or Université de Montreal. In addition to introducing deep learning, we mentioned recent applications of deep learning to neuroscience and how neuroscience is being used to advance deep learning. This latter portion of the presentation would set the tone for the discussions in upcoming meetings where we will talk about these works in further detail.

The unexpected high turnout is really exciting and now we are super pumped for the rest of the series. We really want you to be involved so we can all learn from each other. If you have an idea for a presentation or a paper that would be relevant please please share it with us!

You can find the presentation file in our GitHub repository for this group:

https://github.com/arnaghosh/NDL_MNI/tree/master/Slides