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PUT AI TO WORK
June 18-21, 2019
Beijing, CN

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)

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 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.

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

By the end of this two-day training course, you'll understand:

  • What machine learning, neural networks, deep learning, and artificial intelligence are
  • What TensorFlow is and what applications it's good for

And you'll 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...

  • You're 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 a background in data science, and you would like to learn TensorFlow and deep learning.
  • You're in a nontechnical role, and you'd like to more effectively communicate with the engineers and data scientists in your company about TensorFlow and neural networks.

Prerequisites:

  • Familiarity with the Python language, matrices, modeling, and statistics

Outline

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 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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Comments

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

Thomas Hainzl | HEAD OF DIGITAL ENABLEMENT PLATFORMS
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.

RAMANATHAN RAMAKRISHNAN |
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?