Deep Learning with PyTorch : Build an AutoEncoder
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Deep Learning with PyTorch : Build an AutoEncoder

Highlights

In these one hour project-based course, you will learn to implement autoencoder using PyTorch. An autoencoder is a type of neural network that learns to copy its input to its output. In autoencoder, encoder encodes the image into compressed representation, and the decoder decodes the representation to reconstruct the image. We will use autoencoder for denoising hand written digits using a deep learning framework like pytorch. This guided project is for learners who want to use pytorch for building deep learning models.Learners who want to apply autoencoder practically using PyTorch. In order to be successful in this project, you should be familiar with python , basic pytorch like creating or defining neural network and convolutional neural network.

About the Course Provider

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Course by

  • self
    Self paced
  • dueration
    Duration 3 hours
  • domain
    Domain IT & Computer Science
  • subs
    Monthly Subscription Option not available
  • fee
    Buy Now Free
  • language
    Language English