Mar 15–18, 2020

Deep learning with PyTorch (Day 2)

Rich Ott (The Pragmatic Institute)
Location: 113

Level

Intermediate

Outline

Day 1

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

Day 2

  • Network architectures
  • Convolutional neural network
  • Autoencoders

Prerequisite knowledge

  • A basic understanding of Python, matrices and linear algebra, modeling and machine learning, and neural networks

What you'll learn

  • Understand PyTorch's tensors and automatic differentiation package
  • Examine different deep learning model architectures
  • Learn to build and train deep neural networks in PyTorch
Photo of Rich Ott

Rich Ott

The Pragmatic Institute

Richard Ott obtained his PhD in particle physics from the Massachusetts Institute of Technology, followed by postdoctoral research at the University of California, Davis. He then decided to work in industry, taking a role as a data scientist and software engineer at Verizon for two years. When the opportunity to combine his interest in data with his love of teaching arose at The Data Incubator, he joined and has been teaching there ever since.

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