Sep 9–12, 2019

Deep Learning with PyTorch

Rich Ott (The Data Incubator)
Monday, Sep 9 & Tuesday, Sep 10,
9:00am - 5:00pm
Location: 112

Participants should plan to attend both days of this 2-day training course. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Tuesday.

PyTorch is a machine learning library for Python that allows users 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. This course will introduce the PyTorch workflow and demonstrate how to use it. Students will be equipped with the knowledge to build deep learning models using real-world datasets.

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

  • PyTorch's tensors and automatic differentiation package
  • Building and training deep neural networks in PyTorch
  • Different deep learning model architectures

This training is for you because...

Developers and analysts with some machine learning and python experience

Prerequisites:

Basic knowledge of the following topics:

  • Python
  • Matrices and linear algebra
  • Modeling and machine learning
  • Basic neural networks

Hardware and/or installation requirements:

N/A

Day 1:

  • PyTorch tensors
  • Automatic differentiation package
  • Neural Networks
  • Multilayer Perceptrons

Day 2:

  • Network architectures,
  • Convolutional Neural Network
  • Auto-Encoders

About your instructor

Photo of Rich Ott

Richard Ott is a data scientist in residence at the Data Incubator, where he gets to combine 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.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package. Early Price ends July 26.

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