Deep learning with TensorFlow

Season Yang (McKinsey & Company)
Tuesday, June 18 & Wednesday, June 19, 09:00 - 17:00
与人工智能交互 (Interacting with AI)
Location: 多功能厅5A+B(Function Room 5A+B)
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.


Day 1

  • Introduction to TensorFlow
  • Iterative algorithms
  • Machine learning
  • Basic neural networks

Day 2

  • Deep neural networks
  • Variational autoencoders
  • Convolutional neural networks
  • Adversarial noise
  • DeepDream
  • Recurrent neural networks


Photo of Season Yang

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.


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Season Yang |
2019-06-12 08:08 CST

You will need your laptop with you and the whole courses will be hand-on practice on your laptop. No prerequisites are required

2019-06-12 08:05 CST

In order to attend the workshop do I have to take a laptop with me? Are there any HW/SW prerequisites?
Or will a computer be provided on site.

2019-05-29 09:02 CST

My vision is to develop an OS for AI which could emulate diverse human personalities in machines. How could I go about it? Do you support in any way?