Abstract: 

Some of the most exciting tech research happening now is in the area of deep learning, but how do we get started with hands-on practice and how do we gain a basic understanding of what is going on within all of those deep learning layers?

This lesson will help a beginner navigate this new landscape. We’ll start by identifying some of the major breakthroughs that make deep learning what it is today. Then we’ll get a chance to learn about the math and architecture behind neural nets. Lastly, we’ll talk about how you can create and tune your own neural networks via Keras.

Bio: 

Julia Lintern currently works as an instructor for the Metis Data Science Flex Program. Previously, she worked as a Data Scientist for the New York Times. Julia began her career as a structures engineer designing repairs for damaged aircraft. Julia holds an MA in applied math from Hunter College, where she focused on visualizations of various numerical methods and discovered a deep appreciation for the combination of mathematics and visualizations. During certain seasons of her career, she has also worked on creative side projects such as Lia Lintern, her own fashion label.