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

4.7
stars
1,913 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

MS

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great course, only teaching what's needed, doesn't push you a lot in the coding assignments, as much as it requires you much more work to understand the codes and the science behind it.

KM

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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

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176 - 200 of 446 Reviews for Build Basic Generative Adversarial Networks (GANs)

By Sina A

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Dec 30, 2020

Very well-organized course with easy to grasp lectures and deepening assignments.

By MICHAEL D S R

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Oct 25, 2020

Excellent course management! But it is a bit too fast for non-english speakers :)

By José J F G V

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Jan 6, 2022

Good Course. I enjoy how the instructors adapt theory with practical exercises.

By Shahir A

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Jun 14, 2021

Thank you so much Coursera. The teacher was amazing. The problems were as well.

By Priscilla P L

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Jan 23, 2021

Sharon's videos are so polished and digestible. Everything is explained so well.

By Luiza P

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Aug 21, 2021

I love deeplearning.ai courses! The content and teachers are always of quality.

By Alessio S

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Jul 1, 2021

Useful also to understand many other aspects of Neural Networks, not only GANs.

By Michael E

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May 1, 2021

This course was an eye opener and I have had a better understanding of GANs now

By Fairuz F S

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Apr 26, 2021

Its so excited to finish this course and i also learn this for my final project

By Gokulakannan S

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Dec 9, 2020

Nice Course but the interpolation technique didn't work in Week 4 assignment 1.

By W F (

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Nov 3, 2020

Good content. Assignments are made to be doable in a reasonable amount of time.

By manohar2000

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Oct 17, 2020

Excellent and disentangled course like the style gan. Really neat explanations.

By Diego M G S

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Oct 7, 2020

una profesora increíble, muy facil de entender la teoria, no tanto las formulas

By Mark T

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Nov 11, 2021

great content. Feel like I learned a lot, and coding labs were useful as well.

By Marcin Z

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Nov 26, 2020

Great course, much better than NLP one. They use PyTorch here which is a plus.

By Vishal K

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Nov 18, 2020

Excellent course to understand the basics of GAN and also do cool assignments!

By Blanca H V G

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Dec 18, 2020

Great course. Sharon is a good teacher. Thank you for all material and codes!

By Sangeeta O

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Nov 8, 2021

Excellent course with basic of GAN ,loss functions and types of GAN covered

By Adam R R - A

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Nov 16, 2020

This was a pretty simple, understandable introduction to GANs. I enjoyed it.

By brightmart

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Oct 7, 2020

Excellent! Easy to understand, and can get hand-on experience of basic GANs.

By MiÄ·elis P

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Jan 25, 2024

All topics were intuitively and visually well explained, valuable course!

By pasha s

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Feb 16, 2022

Assigngnmets make you think deeply and understand the concepts thoroughly

By YASI Z

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Sep 27, 2022

Nice explanation. Looking forward to following courses in this series.

By Horváth K

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Apr 9, 2021

I wish I could have the same quality courses at my university as well.

By Swathi K

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Mar 7, 2023

Really good and was explained in very detail and understanding manner