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

Tom Hope
Data Scientist and Applied Researcher, Independent

Tom Hope is an applied machine-learning researcher and data scientist. Tom has an extensive background as a senior data scientist for large, international corporations, where he has led data science and deep learning R&D across multiple domains, including web mining, text analytics, computer vision, sales and marketing, the IoT, financial forecasting, and large-scale manufacturing. Previously, Tom was at ecommerce startup Tapingo in its early days, where he led data science R&D. He has also served as a data science consultant for major international companies and startups. Tom’s academic research and publications in computer science, data mining, and statistics revolve around machine learning, deep learning, NLP, weak supervision, and time series.


9:00am - 5:00pm Monday, May 8 & Tuesday, May 9
Location: Meeting Room 7
Level: Intermediate
Tom Hope (Independent), Itay Lieder (Independent), Yehezkel Resheff (Independent)
Average rating: ****.
(4.00, 1 rating)
Tom Hope, Itay Lieder, and Yehezkel Resheff walk you through the fundamental concepts of deep learning and explain how to build production-ready AI systems with TensorFlow, the leading software framework for building machine intelligence systems with deep learning. Read more.