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Learner Reviews & Feedback for Build Basic Generative Adversarial Networks (GANs) by DeepLearning.AI

4.7
stars
1,877 ratings

About the Course

In this course, you will: - Learn about GANs and their applications - Understand the intuition behind the fundamental components of GANs - Explore and implement multiple GAN architectures - Build conditional GANs capable of generating examples from determined categories The DeepLearning.AI Generative Adversarial Networks (GANs) Specialization provides an exciting introduction to image generation with GANs, charting a path from foundational concepts to advanced techniques through an easy-to-understand approach. It also covers social implications, including bias in ML and the ways to detect it, privacy preservation, and more. Build a comprehensive knowledge base and gain hands-on experience in GANs. Train your own model using PyTorch, use it to create images, and evaluate a variety of advanced GANs. This Specialization provides an accessible pathway for all levels of learners looking to break into the GANs space or apply GANs to their own projects, even without prior familiarity with advanced math and machine learning research....

Top reviews

KM

Jul 20, 2023

Helped me clarify the some of key principles and theories behind GAN and bit of history... The references/additional study materials are very useful, if you want to dig deep into. Overall very pleased

HL

Mar 10, 2022

Great introductory to GANs, focused on the building blocks to neural net/ GANs, and a bit of frequently used models. Might need a small update on what's considered "state-of-the-art" in the course.

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426 - 439 of 439 Reviews for Build Basic Generative Adversarial Networks (GANs)

By Bedrich P

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Aug 21, 2021

I don't like the style of programming assignments, otherwise good

By Michael K

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Oct 12, 2020

Great intuitive explanations but it is too easy

By Keebeom Y

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Aug 17, 2021

She talks too fast! Please slow down!

By Christoffer M

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Mar 4, 2021

The GANs in the course are basic as advertised, but unfortunately the treatment of the theory is basic and shallow as well. The lab assignments are too simplistic to force any deeper understanding.

By Shiblee S

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Aug 24, 2023

The assignment on the week 3 didn't compile. Probably some version mismatch issue.

The instructor didn't go into the details of the some of the key concept, they kept it very vague

By Daniil K

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Aug 28, 2021

The course if very interesting, but unfortunately after the completion you lose the access to assignments and the only way to restore it is to subscribe again.

By Fatemeh A

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Jun 11, 2021

It was too high level without mentioning the math behind the theories. The codes were too simple and not challenging. The instructor was speaking too fast.

By Yu G

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Jan 17, 2021

Homework size are TOO large! One star given. One additional for that this course is highly challenging.

By Brian M

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Mar 6, 2023

Not much value in auditing this class w/o access to the coursework itself.

By Alexander K

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Jun 3, 2023

After week 1, not sure what the objective of this course is, seems this is more about PyTorch.

The course material about the concept of GANs is actually quite good, but the assignments are near impossible for me as I am not a PyTorch expert. Trying to figure out the syntax, not really what I was looking for.

A couple of years back, I completed one of their earlier courses (Machine Learning) and it didn’t use any language, but essentially a MatLab like environment to manipulate matrices and vectors.

No sweat, I’ll just cancel the subscription and find another way to learn this stuff.

By Ranga R S

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Feb 11, 2021

Had to pause multiple times to listen again or read the English translation at the bottom. Slowing down the lecture along with proper pauses and meaningful visual illustrations can improve this course in a big way.

Content of this course is good, but the way it is presented leaves much to be desired

By Michael S

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Feb 7, 2021

The coding exercises seem completely unguided by the course, and feel like a waste of my time.

I'm not going to pay you for the time I spend studying pytorch.org

By joseph z

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May 15, 2023

thanks for the hard work, but I feel a lot of places not explained clearly, and the assignment is also not that helpful

By Scott A

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Jul 20, 2021

Way, way, way too light on the details