Hands-On Generative Adversarial Networks with PyTorch
INTERACTIVE COURSE

Hands-On Generative Adversarial Networks with PyTorch

Advanced

55 Lessons

16h

Certificate of Completion

AI Explanations
AI Explanations
AI Feedback
AI Feedback
AI Prompt
AI Prompt
Hands-On Generative Adversarial Networks with PyTorch
29 Playgrounds
10 Quizzes
101 Illustrations

Takeaway Skills

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 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

Course Content

1

Getting Started

2

Generative Adversarial Networks Fundamentals

3

Best Practices for Model Design and Training

4

Building Our First GAN with PyTorch

5

Generating Images Based on Label Information

6

Image-to-Image Translation and Its Applications

5 Lessons

7

Image Restoration with GANs

6 Lessons

8

Training GANs to Break Different Models

3 Lessons

9

Image Generation from Description Text

5 Lessons

10

Sequence Synthesis with GANs

4 Lessons

11

Reconstructing 3D Models with GANs

3 Lessons

12

Concluding Remarks

1 Lesson

13

Appendix

7 Lessons

COURSE AUTHOR

How You'll Learn

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Progress You Can Show

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