Back to Deep Learning with PyTorch : Generative Adversarial Network
Learner Reviews & Feedback for Deep Learning with PyTorch : Generative Adversarial Network by Coursera Project Network
87 ratings
About the Course
In this two hour project-based course, you will implement Deep Convolutional Generative Adversarial Network using PyTorch to generate handwritten digits. You will create a generator that will learn to generate images that look real and a discriminator that will learn to tell real images apart from fakes. This hands-on-project will provide you the detail information on how to implement such network and train to generate handwritten digit images.
In order to be successful in this project, you will need to have a theoretical understanding on convolutional neural network and optimization algorithm like Adam or gradient descent. This project will focus more on the practical aspect of DCGAN and less on theoretical aspect.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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1 - 7 of 7 Reviews for Deep Learning with PyTorch : Generative Adversarial Network
By VEENASANATHKUMAR
•Oct 25, 2021
GOOD COURSE
By Kevin Y H Z
•Apr 5, 2025
+100
By Neha T
•Dec 7, 2021
Good
By Harith Y
•May 29, 2025
Felt like the instructor was rushing in the last 3 videos, and he did not explain it completely in detail. Rest was very good
By Meena
•Jul 31, 2022
Very Helpful
By pranita k
•Jul 21, 2023
wow
By Majid A S
•Sep 9, 2023
This is a good, short course as the form of project to review and recap what you already knew in Deep Learning using PyTorch.