Presented By

June 18-21, 2019
Beijing, CN

In-Person Training
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)

This course will sell out—sign up today!

See passes & pricing
Early Price ends May 10

Participants should plan to attend both days of this 2-day training course. Platinum and Training passes do not include access to tutorials on Wednesday.

The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. This training will introduce TensorFlow's capabilities in Python. It will move from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications.

What you'll learn, and how you can apply it

Participants will understand:
  • What machine learning, neural networks, deep learning, and artificial intelligence are.
  • What TensorFlow is and what applications it is good for.
Participants will be able to:
  • Create deep learning models for classification and regression using TensorFlow.
  • Evaluate the benefits and disadvantages of using TensorFlow over other machine learning software.

This training is for you because...

This workshop is for you if: You are a software engineer or programmer with a background in Python, and you wish to develop an understanding of machine learning. You have experience modeling or have a background in data science, and you would like to learn TensorFlow and deep learning You are in a non-technical role, and you would like to more effectively communicate with the engineers and data scientists in your company about TensorFlow and neural networks.


  • Familiar with Python language
  • Familiarity with matrices
  • Familiarity with modeling
  • Familiarity with statistics
No experience with TensorFlow is required.

Hardware and/or installation requirements:


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

About your instructor

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 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.


Get the Platinum pass or the Training pass to add this course to your package. Early Price ends May 10.

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