UD
4.0Reviewed Nov 23, 2020
I think this course has more advanced "tricks" and models that are supported with fewer assignments, which could be one shortcoming of the course.
Build Better Generative Adversarial Networks (GANs)
In this course, you will: - Assess the challenges of evaluating GANs and compare different generative models - Use the Fréchet Inception Distance (FID) method to evaluate the fidelity and diversity of GANs - Identify sources of bias and the ways to detect it in GANs - Learn and implement the techniques associated with the state-of-the-art StyleGANs 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.
Status: Machine Learning
Status: Image Quality
IntermediateCourse29 hours
Featured reviews
JM
5.0Reviewed Apr 22, 2021
Me gustaron mucho los temas en general, aunque me gustaría que en los videos hablen de las dimensiones de los tensores, a mí eso me ayudaría mucho a entender rápido
BK
5.0Reviewed Mar 4, 2021
Good course and flexible! Quick if you want that but lots of references to the papers if you want depth.
AB
5.0Reviewed Mar 24, 2021
Great material...but the stylegan code implementation requires more video material. Instead adding one more week for ProGan part before stylegan would be helpful for the learners.
MZ
5.0Reviewed Mar 12, 2022
This course reignited my interest in and passion about ML. I can hardly imagine the much I dont know that awaits me out there! I can barely wait for the third course!
JK
5.0Reviewed Feb 18, 2021
I liked this course. The exercises were easy to follow and the lectures were also simple and well organized.
HD
5.0Reviewed Jul 30, 2024
The course content was well-structured, making complex concepts easy to understand. Thank you for the great course.
MM
5.0Reviewed Oct 16, 2020
Week2 is little diverged, but concise detailed understanding explanation of style GAN is excellent. It is really worth.
AS
5.0Reviewed Jan 15, 2021
Build state of the art models in a course is not an easy feat. Thanks to all the materials that have been provided.
MB
5.0Reviewed Aug 25, 2023
This course has helped me to dive deeper into the world of Generative AI through GANs and know what they can do and what are the advantages, benefits and disadvantages at the same time.
AM
4.0Reviewed Nov 7, 2020
Greate course content and assignments but I want to give one feedback to the instructor. Please keep some pause while speaking. She speaks way too fast.
LG
5.0Reviewed Jan 28, 2021
Great course, short and to the point. Well explained by Sharon and the excercise and graded assignments make you understand the subject matter even better.