Making Open Work
May 8–9, 2017: Training & Tutorials
May 10–11, 2017: Conference
Austin, TX
Aaron Schumacher

Aaron Schumacher
Senior Data Scientist and Software Engineer, Deep Learning Analytics

Website | @planarrowspace

Aaron Schumacher is a data scientist and software engineer for Deep Learning Analytics. He has taught with Python and R for General Assembly and the Metis data science bootcamp. Aaron has also worked with data at Booz Allen Hamilton, New York University, and the New York City Department of Education. In his spare time, Aaron is a breakdancer. His career-best result was advancing to the semifinals of the R16 Korea 2009 individual footwork battle. He is honored to be the least significant contributor to TensorFlow 0.9.

Sessions

9:00am12:30pm Tuesday, May 9, 2017
Adopt This Now, TensorFlow
Location: Meeting Room 12
Level: Intermediate
Aaron Schumacher (Deep Learning Analytics)
Average rating: ***..
(3.25, 8 ratings)
Aaron Schumacher takes a building-block approach to exploring the tools TensorFlow provides so you can build the systems you need and write your own TensorFlow—not just run other people's scripts. Aaron discusses the many aspects of TensorFlow—including data management, machine learning, distribution, and serving—by comparing them with similar functionality in other toolkits. Read more.
11:50am12:10pm Wednesday, May 10, 2017
Location: Meeting Room 16
Aaron Schumacher (Deep Learning Analytics)
Average rating: ****.
(4.50, 2 ratings)
Arlington-based Deep Learning Analytics has built products with toolkits ranging from cuda-convnet to TensorFlow. Systems built on Caffe have matured and provide points of reference for comparison. Aaron Schumacher explains why TensorFlow is being chosen for more projects based on design strengths and features that will support future growth. Read more.