Image analysis and text classification using CNNs in PyTorch : learn to build powerful image and document classifiers in minutes

Resource Information

The work Image analysis and text classification using CNNs in PyTorch : learn to build powerful image and document classifiers in minutes represents a distinct intellectual or artistic creation found in Merrimack Valley Library Consortium. This resource is a combination of several types including: Work, Still Image, Visual Materials.

Label

Image analysis and text classification using CNNs in PyTorch : learn to build powerful image and document classifiers in minutes

Title remainder

learn to build powerful image and document classifiers in minutes

Statement of responsibility

with Goku Mohandas and Alfredo Canziani

Creator

• Mohandas, Goku

Contributor

• Canziani, Alfredo

Subject

• Artificial intelligence
• Machine learning
• Neural networks (Computer science)
• Python (Computer program language)

Language

eng

Summary

"This video teaches you how to build a powerful image classifier in just minutes using convolutional neural networks and PyTorch. It reviews the fundamental concepts of convolution and image analysis; shows you how to create a simple convolutional neural network (CNN) with PyTorch; and demonstrates how using transfer learning with a deep CNN to train on image datasets can generate state-of-the-art performance. The course is designed for the software engineer looking to get started with deep learning and for the AI researcher with TensorFlow or Theano experience who wants a smooth transition into PyTorch. Prerequisites include an understanding of algebra, basic calculus, and basic Python skills. Learners should download and install PyTorch before starting class."--Resource description page

Cataloging source

UMI

Characteristic

videorecording

http://bibfra.me/vocab/relation/on-screenpresenter

• q5HtP5BWbgI
• uw2UymbRG8o

PerformerNote

Presenters, Goku Mohandas, Alfredo Canziani

Runtime

55

Technique

live action