返回到 Deep Learning with PyTorch : Neural Style Transfer
学生对 Coursera Project Network 提供的 Deep Learning with PyTorch : Neural Style Transfer 的评价和反馈
80 个评分
课程概述
In this 2 hour-long project-based course, you will learn to implement neural style transfer using PyTorch. Neural Style Transfer is an optimization technique used to take a content and a style image and blend them together so the output image looks like the content image but painted in the style of the style image. We will create artistic style image using content and given style image. We will compute the content and style loss function. We will minimize this loss function using optimization techniques to get an artistic style image that retains content features and style features.
This guided project is for learners who want to apply neural style transfer practically using PyTorch.
In order to be successful in this guided project, you should be familiar with the theoretical concept of neural style transfer, python programming, and convolutional neural networks.A google account is needed to use the Google colab environment.
热门审阅
IP
Jan 6, 2022
great guided project , learn NST, pytorch, vgg architecture before starting and there are some exceptions in the code feel free to search in stackoverflow.
VM
Dec 16, 2020
The understanding in this course is amazing and very satisfying. I will recommended to my friends to take this one.
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1 - Deep Learning with PyTorch : Neural Style Transfer 的 16 个评论（共 16 个）
创建者 Jose L M M
•Jun 13, 2021
创建者 Immadi S P
•Jan 7, 2022
创建者 Vatsal K M
•Dec 17, 2020
创建者 JODHANI Z
•Feb 22, 2021
创建者 Kartik D
•Jan 16, 2021
创建者 19020587 P H N
•Dec 18, 2021
创建者 Sania Z
•Sep 27, 2021
创建者 Gabriel F
•Sep 14, 2021
创建者 Huyy N
•Jul 12, 2021
创建者 Kenneth N
•Jul 28, 2022
创建者 2K19/MC/131 T K
•Nov 18, 2021
创建者 Yutaro O
•May 14, 2021
创建者 Monish
•Aug 5, 2021
创建者 Jung S
•Sep 17, 2021
创建者 Frank W
•Nov 2, 2021
创建者 Christos G
•Dec 6, 2020
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