Introduction to Deep Learning
In the past decade, neural networks have become a valuable tool for data scientists, revolutionizing fields such as text processing, image analysis, genomic/proteomic data analysis, data clustering, and much more. However, these algorithms can be very difficult to understand, interpret, and program. This workshop will first cover the theory and proper applications of various neural networks (multilayer perceptrons, convolutional neural networks, long-short term memory models, autoencoders, etc.). From there, powerful deep learning packages, such as Pytorch and Keras, will be introduced. Proper coding techniques will be shown through examples and practiced through exercises that will be completed in the Python 3 programming language. Finally, concepts in data visualization and software engineering will be discussed, helping researchers use neural networks in an effective and reproducible way to improve the impact of projects with a computational component.