Advanced
55 Lessons
16h
Certificate of Completion
AI-POWERED
This course includes
This course includes
Course Overview
Generative Adversarial Networks (GANs) are a class of machine learning models used to generate data resembling a given dataset. In a GAN, two neural networks, the generator and discriminator, compete. PyTorch is a popular deep learning (DL) framework that is efficient for GAN implementation due to its dynamic computation capabilities. The course begins with GAN basics, activation functions, and model training best practices. You’ll build your first GAN with PyTorch, exploring DCGANs and conditional GANs. T...Show More
What You'll Learn
Knowledge of GAN fundamentals and PyTorch features
Hands-on experience building GANs with PyTorch
Proficiency in model design and training
An understanding of adversarial learning and breaking different models
Application of GANs in diverse domains like computer vision and NLP
Familiarity with training challenges, required resources, and their results
Course Content
Getting Started
Generative Adversarial Networks Fundamentals
Best Practices for Model Design and Training
Building Our First GAN with PyTorch
Generating Images Based on Label Information
Image-to-Image Translation and Its Applications
5 Lessons
Image Restoration with GANs
6 Lessons
Training GANs to Break Different Models
3 Lessons
Image Generation from Description Text
5 Lessons
Sequence Synthesis with GANs
4 Lessons
Reconstructing 3D Models with GANs
3 Lessons
Concluding Remarks
1 Lesson
Appendix
7 Lessons
How You'll Learn
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