Why you can't afford to ignore deep lear...

Few involved in life sciences have a background in the neural network fundamentals that underpin deep learning, and that can make it quite overwhelming when trying to learn about this topic for the first time. And it doesn't help that there's so much breathless hype around, which makes it hard to know what opportunities are real, and what is just marketing. I came to deep learning applications in the life sciences from the other direction - although I've been working with neural networks for around 25 years, I only started looking at life sciences applications in the last couple of years. The data in life sciences tends to be challeging to work with - generally unstructured (genome sequences, natural language text, imaging, sound, etc) and often data sets are quite large. This kind of data turns out to be where deep learning really shines. In fact, many classic approaches to data analysis in the life sciences are either in the process of, or are about to be, totally transformed by deep learning.  In this talk, I'll describe what deep learning can do, and give some examples of how it can be applied, with a particular focus on medical applications. I'll also provide some suggested places to learn more, so if I'm successful in my goal to convince you that you can't afford to ignore deep learning, you'll know where to look next.