June 18-21, 2019
Beijing, CN
Season Yang

Season Yang
Analytics Fellow, McKinsey & Company

Season Yang is an analytics fellow in McKinsey & Company’s risk practice. Previously, Season was a data scientist in residence at the Data Incubator, where he also contributes to curriculum development and instruction, and worked at NASA’s Goddard Space Flight Center, where he studied climate change models with data analysis. Season holds a double bachelor’s degree in applied mathematics and scientific computation and economics from UC Davis and a master’s in applied mathematics from Columbia, specializing in numerical computation.


09:00 - 17:00 Tuesday, June 18 & Wednesday, June 19
与人工智能交互 (Interacting with AI)
Location: 多功能厅5A+B(Function Room 5A+B)
Season Yang (McKinsey & Company)
Average rating: *****
(5.00, 1 rating)
The TensorFlow library contains computational graphs with automatic parallelization across resources, which is ideal architecture for implementing neural networks. Season Yang introduces TensorFlow's capabilities in Python, and you'll then get your hands dirty building machine learning algorithms piece by piece while using the Keras API provided by TensorFlow with several hands-on applications. Read more.