Mar 15–18, 2020

Deep learning with PyTorch

Ana Hocevar (The Data Incubator)
9:00am—5:00pm
Sunday, March 15—Monday, March 16
Location: 113

Participants should plan to attend both days of training course. Note: to attend training courses, you must be registered for a Platinum or Training pass; does not include access to tutorials on Monday.

PyTorch is a machine learning library for Python that allows you to build deep neural networks with great flexibility. Its easy-to-use API and seamless use of GPUs make 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 and PyTorch with Ana Hocevar.

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

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

Level

Intermediate

Prerequisites:

  • A basic understanding of Python, matrices and linear algebra, modeling and machine learning, and 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 Ana Hocevar

Ana Hocevar is a data scientist in residence at the Data Incubator, where she combines her love for coding and teaching. Ana has more than a decade of experience in physics and neuroscience research and over five years of teaching experience. Previously, she was a postdoctoral fellow at the Rockefeller University, where she worked on developing and implementing an underwater touch screen for dolphins. She holds a PhD in physics.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package. Early Price ends February 7.

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