Deep Learning with PyTorch
9:00am - 5:00pm
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...
Basic knowledge of the following topics:
- Matrices and linear algebra
- Modeling and machine learning
- Basic neural networks
Hardware and/or installation requirements:
- PyTorch tensors
- Automatic differentiation package
- Neural Networks
- Multilayer Perceptrons
- Network architectures,
- Convolutional Neural Network
About your instructor
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.
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