Deep learning with PyTorch
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
Who is this presentation for?
- You're a developer or analyst with some machine learning and Python experience.
- A basic understanding of Python, matrices and linear algebra, modeling and machine learning, and neural networks
- 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 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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