HomeCoursesHands-On Generative Adversarial Networks with PyTorch

Advanced

16h

Updated 4 months ago

Hands-On Generative Adversarial Networks with PyTorch
Save

In this GAN course, learn GAN fundamentals and PyTorch. Explore DCGANs, conditional GANs, image translations, and text-to-image synthesis to master advanced skills for real-world applications.

Join 2.7 million developers at

Overview

Content

Reviews

Generative adversarial networks (GANs) are machine learning models that generate data resembling a given dataset. GANs have two neural networks: the generator and the discriminator. PyTorch is a popular deep learning framework that is efficient for GAN implementation due to its dynamic computation capabilities. The course begins with what are GANs, activation functions, and model training best practices. You’ll build your first GAN with PyTorch, exploring DCGANs and conditional GANs. Then, you’ll learn image generation with label info, image-to-image translation with pix2pix and CycleGAN, and image restoration techniques. The course concludes with text-to-image synthesis, sequence synthesis, and 3D model reconstruction, providing a comprehensive understanding of GANs. This course equips developers with advanced GAN and DL skills. Mastering GANs using PyTorch will enable you to tackle real-world challenges in various domains like image processing and multimedia content generation.

Generative adversarial networks (GANs) are machine learning models that generate data resembling a given dataset. GANs have two ...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

Knowledge of GAN fundamentals and PyTorch features

Content

55 Lessons10 Quizzes

Getting Started

1 Lessons

Get familiar with GANs, their architecture, and hands-on applications using PyTorch.

Introduction to the Course

Generative Adversarial Networks Fundamentals

5 Lessons

Discover the logic behind GANs, their adversarial process, functions, and diverse applications.

Fundamentals of Machine Learning

Introducing Adversarial Learning

Defining Activation Functions and The Loss Function

What Can GANs Do?

Quiz: Generative Adversarial Network Fundamentals

Best Practices for Model Design and Training

5 Lessons

Go hands-on with designing and training GANs, optimizing parameters, and efficient coding in Python.

Model Design Cheat Sheet

Parameter and Loss Function

Optimizations and Learning Rate

Efficient Coding in Python

Quiz: Best Practices for Model Design and Training

Building Our First GAN with PyTorch

5 Lessons

Apply your skills to build, train, and explore DCGANs with PyTorch for image generation.

Introduction to Deep Convolutional GANs

Creating a DCGAN with PyTorch

Moving to Larger Datasets

Having Fun with the Generator Network

Quiz: Building Our First GAN with PyTorch

Generating Images Based on Label Information

5 Lessons

Solve problems in generating labeled images using CGANs, Fashion-MNIST, and InfoGAN.

CGANs: How Are Labels Used?

Generating Images from Labels with the CGAN

Working with the Fashion-MNIST Dataset

InfoGAN—Unsupervised Attribute Extraction

Quiz: Generating Images Based on Label Information

Image-to-Image Translation and Its Applications

5 Lessons

Tackle image-to-image translation models, including pix2pix, pix2pixHD, and CycleGAN applications.

Using Pixel-Wise Labels to Translate Images with pix2pix

Training and Evaluation of pix2pix

Pix2pixHD: High-Resolution Image Translation

CycleGAN: Image-to-Image Translation from Unpaired Collections

Quiz: Image-to-image Translation from Unpaired Collections

Image Restoration with GANs

6 Lessons

Practice using GANs for super-resolution, inpainting, and enhancing image quality with SRGAN and WGAN.

Image Super-Resolution with SRGAN

Training SRGAN to Generate High-Resolution Images

Generative Image Inpainting

WGAN—Understanding the Wasserstein Distance

Training GAN for image inpainting

Quiz: Image Restoration with GANs

Training GANs to Break Different Models

3 Lessons

Step through creating adversarial examples using GANs to challenge deep learning models.

Adversarial Examples: Attacking Deep Learning Models

Generative Adversarial Examples: Working with Classifier

Quiz: Training GANs to Break Different Models

Image Generation from Description Text

5 Lessons

Get started with text-to-image synthesis using GANs, advanced architectures, and StackGAN++.

Text-to-Image Synthesis with GANs

GAN Architecture and Training

Generating Photo-Realistic Images with StackGAN++

Training StackGAN++ to Generate Images with Better Quality

Quiz: Image Generation from Description Text

10.

Sequence Synthesis with GANs

4 Lessons

Go hands-on with SeqGAN for text generation and SEGAN for speech enhancement.

Text Generation via SeqGAN

Creating Our Vocabulary for Training

Speech Quality Enhancement with SEGAN

Quiz: Sequence Synthesis with GANs

11.

Reconstructing 3D Models with GANs

3 Lessons

Enhance your skills in 3D object representation, GANs design, and training techniques.

Fundamental Concepts in Computer Graphics

Designing GANs for 3D Data Synthesis

Quiz: Reconstructing 3D Models with GANs

12.

Concluding Remarks

1 Lessons

Equip yourself with essential GAN knowledge and hands-on PyTorch skills for real-world applications.

Conclusion

13.

Appendix

7 Lessons

Tackle installing PyTorch, setting up GPU acceleration, and exploring the C++ frontend for efficient training.

Introduction to PyTorch

Required Downloads

The C++ Frontend

CUDA—GPU Acceleration for Fast Training and Evaluation

Installing PyTorch on Windows and Linux

Checking GPU Usage Information

Steps to Reach the C++ Source Code for nn.PixelShuffle

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Packt

Developed by MAANG Engineers

Every Educative resource is designed by our in-house team of ex-MAANG software engineers and PhD computer science educators — subject matter experts who’ve shipped production code at scale and taught the theory behind it. The goal is to get you hands-on with the skills you need to stay ahead in today's constantly evolving tech landscape. No videos, no fluff — just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

Trusted by 2.7 million developers working at companies

"These are high-quality courses. Trust me. I own around 10 and the price is worth it for the content quality. EducativeInc came at the right time in my career. I'm understanding topics better than with any book or online video tutorial I've done. Truly made for developers. Thanks"

Anthony Walker

@_webarchitect_

"Just finished my first full #ML course: Machine learning for Software Engineers from Educative, Inc. ... Highly recommend!"

Evan Dunbar

ML Engineer

"You guys are the gold standard of crash-courses... Narrow enough that it doesn't need years of study or a full blown book to get the gist, but broad enough that an afternoon of Googling doesn't cut it."

Software Developer

Carlos Matias La Borde

"I spend my days and nights on Educative. It is indispensable. It is such a unique and reader-friendly site"

Souvik Kundu

Front-end Developer

"Your courses are simply awesome, the depth they go into and the breadth of coverage is so good that I don't have to refer to 10 different websites looking for interview topics and content."

Vinay Krishnaiah

Software Developer

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

Adaptive Learning

At various checkpoints throughout Educative courses, you will be prompted to take a quick assessment. Receive a condensed curriculum tailored to your strengths and skill gaps.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!

Free Resources

FOR TEAMS

Interested in this course for your business or team?

Unlock this course (and 1,000+ more) for your entire org with DevPath

Hands-On Generative Adversarial Networks with PyTorch Save

Hands-On Generative Adversarial Networks with PyTorch
Save