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

Deep learning with PyTorch

Rich Ott (The Data Incubator)
Tuesday, June 18 & Wednesday, June 19, 09:00 - 17:00
Location: 多功能厅6A+B (Function Room 6A+B)

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.

PyTorch is a machine learning library for Python that allows users to build deep neural networks with great flexibility. Rich Ott introduces you to the PyTorch workflow and explores how its easy-to-use API and seamless use of GPUs makes it a sought-after tool for deep learning. Join in to get the knowledge you need to build deep learning models using real-world datasets.

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

  • Learn PyTorch's tensors, automatic differentiation package, and different deep learning model architectures
  • Understand how to build and train deep neural networks in PyTorch

This training is for you because...

  • You're a developer or analyst with some machine learning and Python experience.

Prerequisites:

  • A working knowledge of Python, matrices and linear algebra, modeling and machine learning, and the basics of neural networks

Outline

Day 1

  • PyTorch tensors
  • Automatic differentiation package
  • Neural networks
  • Multilayer perceptrons

Day 2

  • Network architectures
  • Convolutional neural network
  • Autoencoders

About your instructor

Photo of Rich Ott

Richard Ott is a data scientist in residence at the Data Incubator, where he combines his interest in data with his love of teaching. Previously, he was a data scientist and software engineer at Verizon. Rich holds a PhD in particle physics from the Massachusetts Institute of Technology, which he followed with postdoctoral research at the University of California, Davis.

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