Topics Covered :
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Understand GAN components, build basic GANs using PyTorch and advanced DCGANs using convolutional layers, control your GAN and build conditional GAN
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Compare generative models, use FID method to assess GAN fidelity and diversity, learn to detect bias in GAN, and implement StyleGAN techniques
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Use GANs for data augmentation and privacy preservation, survey GANs applications, and examine and build Pix2Pix and CycleGAN for image translation
What you will learn in this specialization course
- Build Basic Generative Adversarial Networks (GANs) :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
- Build Better Generative Adversarial Networks (GANs) :In this course, you will learn about 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
- Apply Generative Adversarial Networks (GANs) : In this course, you will learn about Explore the applications of GANs and examine them wrt data augmentation, privacy, and anonymity – Leverage the image-to-image translation framework and identify applications to modalities beyond images – Implement Pix2Pix, a paired image-to-image translation GAN, to adapt satellite images into map routes (and vice versa) – Compare paired image-to-image translation to unpaired image-to-image translation and identify how their key difference necessitates different GAN architectures – Implement CycleGAN, an unpaired image-to-image translation model, to adapt horses to zebras (and vice versa) with two GANs in one.
After completing each course in specialization and complete the hands-on project, you’ll earn a Certificate.
Course Rating : 4.7
Instructors :Sharon Zhou,Eda Zhou,Eric Zelikman
Offered By :DeepLearning.AI
Can I download Generative Adversarial Networks (GANs) Specialization course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Generative Adversarial Networks (GANs) Specialization course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.com
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Disclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
