In this session we will take a gentle introduction to Deep Learning.

If you have attended a session or read a book on machine learning that did not mention Deep Learning, AI or Neural Networks then it was most likely a shallow machine learning session.

Shallow machine learning is fantastic when you need to have accountability and auditing of your machine learning models. It is great for a lot of problems, but it does require a lot of work up front. That work is feature engineering. Deep Learning is not a silver bullet by any means, but it is quite different to shallow learning and does not require the same degree of feature engineering. Neural nets, the magic behind deep learning can be shaped to work for all sorts of problems, text generation, image processing, dynamic generation, you name it, there is a neural network trying to solve it.

In this session we will look at the basics of Deep Learning. What is it, why is it deep, what problems does is solve, how do you get started and more. There is an assumption that you know a bit about machine learning, but you will still enjoy the session even if this is your first exposure to machine learning.