Back to Build Basic Generative Adversarial Networks (GANs)
Learner Reviews & Feedback for Build Basic Generative Adversarial Networks (GANs) by DeepLearning.AI
1,968 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 21, 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 11, 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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451 - 452 of 452 Reviews for Build Basic Generative Adversarial Networks (GANs)
By Hunny G
•Sep 24, 2024
how can i create my first GAN without guidence.
By Scott A
•Jul 20, 2021
Way, way, way too light on the details