Sep 23–26, 2019

Dylan Bargteil
Data Scientist in Residence, The Data Incubator

Dylan Bargteil is a data scientist in residence at the Data Incubator, where he works on research-guided curriculum development and instruction. Previously, he worked with deep learning models to assist surgical robots and was a research and teaching assistant at the University of Maryland, where he developed a new introductory physics curriculum and pedagogy in partnership with the Howard Hughes Medical Institute (HHMI). Dylan studied physics and math at the University of Maryland and holds a PhD in physics from New York University.

Sessions

9:00am - 5:00pm Monday, September 23 & Tuesday, September 24

Location: 1E 07

Machine learning from scratch in TensorFlow

Data Science, Machine Learning, & AI

Secondary topics: Deep dive into specific tools, platforms, or frameworks, Deep Learning

Dylan Bargteil (The Data Incubator)

The TensorFlow library provides for the use of computational graphs with automatic parallelization across resources. This architecture is ideal for implementing neural networks. Dylan Bargteil explores TensorFlow's capabilities in Python, demonstrating how to build machine learning algorithms piece by piece and how to use TensorFlow's Keras API with several hands-on applications. Read more.

Location: 1E 07