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學生對 提供的 Build Basic Generative Adversarial Networks (GANs) 的評價和反饋

1,513 個評分


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....




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.



The course provides good insight into the world of GANs. I really enjoyed Sharon's explanations which were deep and easy to understand. I really recommend this course to anyone interested in AI.


301 - Build Basic Generative Adversarial Networks (GANs) 的 325 個評論(共 372 個)

創建者 Debdulal D


The voice over was pretty fast and hard to understand, so had to do lots of sliding window in video to understand the topics. Otherwise this course is fantastic gateway to understand GAN and it's applicability.

創建者 Sanjay K


The Teacher is awesome the way she explains the concepts through great examples. I wish the exercises were a little bit more handson and independent (most of the code structure is already there).

創建者 Cameron M


Great intro course, the programming assignments were pretty weak in difficulty level, could have had less hand holding there. Excited to get into more high resolution GANs soon!

創建者 Mahmoud T S


A little lacking in technical knowledge. You just get to build a GAN and understand bits and pieces about why it works in very simple terms, little mathematics involved.

創建者 Deleted A


Great course to start building GANs.

I wish more math was included. I realize the math behind this is very complex, and not everyone wants to know about that.

創建者 Xin C


Great examples. Wish there were more reading material that bridged the gap between the papers (very detailed) and the slides (good for exposure to material)

創建者 John F


An excellent course. The only area of improvement I can think of would be to get better intuition on the tensor shapes through the model building code.

創建者 Heinz D


Great: a motivating teacher and well-structured learning material. It would be cool to provide the slide sets and to eliminate the need to use Slack.

創建者 Rob B


Excellent example code and assignments. Overall great course, only suggestion but would be adding a little more depth in the lecture topics.

創建者 Jonas B


Good and quite quick course. Assignments very focused on the innovation of the week, which makes them very short and not very demanding.

創建者 Ranajit S


The course was too good and knowledgable. But I felt the loss calculation of the disentanglement should have been explained in detail.

創建者 Laiba T


There should be some explanation of the assignment's code. The lectures were precise and intresting. I like it. It was informative.

創建者 Priyank N


Sharon Nailed it on the insights and the intutions behind every concept discussed and their visual and crisp clarity reasonings

創建者 michael


often felt I could infer what to do an assignment without understanding why I was doing it but generally great course content

創建者 Aleksei


A very good course to understand the basics of how GANs work, but sometimes mathematical explanations were lacking

創建者 Arunava M


I think the videos could have been a bit longer and more technically detailed, nonetheless an enjoyable course!

創建者 Nicholas M C


It would be better if the assignments provided much less of the code, so that people could struggle more.

創建者 Mahmoud S E


C​ritic lessons need to be explained more in details. but overall great course with great instructor.

創建者 Suvojyoti C


Very exciting course content! Only if could give a primer on PyTorch - that would be awesome

創建者 Yudun W


A very easy to understand guide for those who are interested in how GAN generally works!

創建者 Alfredo A


Good intro to the concept felt that some of the excercises were too explicit

創建者 Nicola P


Exceptional theoretical part, but mandatory assignments are way too simple

創建者 Venu V


More help (and annotations) on the code beyond start/end blocks would help

創建者 AlexanderV


Nice course, however with a clear focus on computer vision applications.

創建者 Niraj S


Loving it so far. Kudos to Eda Zhou. She is an excellent instructor.