Please join us this Wed 3/4/20 at 1 pm in DeMeritt Hall Rm. 251 for the latest seminar on machine learning in science.
Dr. Matthew Argall will be talking about Neural Networks:
Machine learning often gets a bad rap for being a “black box”. Data goes in, an answer comes out, and what happens in between is magic. Perhaps no other machine learning algorithm suffers from the black box reputation more than the neural network. In this seminar, we will demystify the neural network by building one from scratch. The concepts of “activation function”, “perceptron”, “feed forward”, and “backward propagation” are introduced. I then present an overview of many of the different types of neural networks that exist. Finally, two applications are presented: a Convolutional Neural Network (CNN) to identify exoplanets and a Long-Short Term Memory (LSTM) Recurrent Neural Network (RNN) to classify plasma boundaries with NASA’s Magnetospheric Multiscale mission.
The jupyter notebook can be downloaded in advance here: https://chapmanlab.github.io/ML/
See you there!