Deep Learning with PyTorch : Build an AutoEncoder
- Offered byCoursera
- Public/Government Institute
Deep Learning with PyTorch : Build an AutoEncoder at Coursera Overview
Deep Learning with PyTorch : Build an AutoEncoder
at Coursera
Duration | 1 hour |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Deep Learning with PyTorch : Build an AutoEncoder
Table of content
- Overview
- Highlights
- Course Details
- Curriculum
Deep Learning with PyTorch : Build an AutoEncoder at Coursera Highlights
Deep Learning with PyTorch : Build an AutoEncoder
at Coursera
- Explore MNIST Handwritten digit dataset
- Data Preparation
- Load Dataset into batches
- Create AutoEncoder Model
- Train AutoEncoder Model
- Plot Results
Read more
Deep Learning with PyTorch : Build an AutoEncoder at Coursera Course details
Deep Learning with PyTorch : Build an AutoEncoder
at Coursera
Skills you will learn
More about this course
- 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.
- SKILLS YOU WILL DEVELOP
- Deep Learning
- Convolutional Neural Network
- Autoencoder
- Python Programming
- Pytorch
Deep Learning with PyTorch : Build an AutoEncoder at Coursera Curriculum
Deep Learning with PyTorch : Build an AutoEncoder
at Coursera
Explore MNIST Handwritten digit dataset
Data Preparation
Load Dataset into batches
Create AutoEncoder Model
Train AutoEncoder Model
Plot Results
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Deep Learning with PyTorch : Build an AutoEncoder
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