Introduction to Deep Learning & Neural Networks II: Practice
Introduction to Deep Learning & Neural Networks II: Practice


In this session, we will focus on the application and practice of building a multi-layer neural network in Python code. We will walk through a lightweight neural network framework and discuss how the concepts from the morning's session were reduced to code, including optimization, regularizerization, and backpropagation. We will step through a concrete example of building an autoencoder for image compression. Participants will have the option to download and run all of the neural network code on their own computers. No GPU required. Participants are also welcome to observe and absorb.

Participating in this workshop you will gain an appreciation for the practical aspects of implementing neural networks, a deeper understanding of how the mechanisms operate, and the tools for building and testing neural networks on your own machine.

No prior experience with neural networks or machine learning required. Prior experience with Python is recommended.


Coming Soon!