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Deep Learning with PyTorch : Build an AutoEncoder(으)로 돌아가기

Coursera Project Network의 Deep Learning with PyTorch : Build an AutoEncoder 학습자 리뷰 및 피드백

4.2
별점
11개의 평가

강좌 소개

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....
필터링 기준:

Deep Learning with PyTorch : Build an AutoEncoder의 3개 리뷰 중 1~3

교육 기관: Bob K

2021년 4월 21일

교육 기관: XZS

2021년 3월 21일

교육 기관: David H

2021년 3월 5일