Apply Generative Adversarial Networks (GANs) from Coursera

In this course, you will:

- 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

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.

What's inside

Syllabus

Week 1: GANs for Data Augmentation and Privacy

Learn different applications of GANs, understand the pros/cons of using them for data augmentation, and see how they can improve downstream AI models!

Week 2: Image-to-Image Translation with Pix2Pix

Understand image-to-image translation, learn about different applications of this framework, and implement a U-Net generator and Pix2Pix, a paired image-to-image translation GAN!

Week 3: Unpaired Translation with CycleGAN

Understand how unpaired image-to-image translation differs from paired translation, learn how CycleGAN implements this model using two GANs, and implement a CycleGAN to transform between horses and zebras!

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores advanced generative adversarial networks including Pix2Pix and CycleGAN

Taught by industry experts and researchers from DeepLearning.AI

Offers hands-on exercises to build practical experience

Covers social implications including bias in ML

Suitable for intermediate learners with a basic understanding of machine learning

Requires knowledge of Python programming and some experience with PyTorch

Reviews summary

Understand gans: concepts, implementation and applications

Learners say this course offers a detailed understanding of GANs and their applications. It provides practical experience in building, training, and evaluating GANs using PyTorch. The course covers advanced GAN architectures, including StyleGANs, and demonstrates their use in domains such as computer vision, multimedia, and natural language processing. While the lectures are highly informative, students have expressed a need for improved explanations and a reduction in the speed of content delivery.

Students learn to evaluate GANs and identify bias.

"Evaluating GANs: You've learned how to evaluate GANs using methods like the Fréchet Inception Distance (FID) to assess the fidelity and diversity of GANs. You've also learned how to identify and detect bias in GANs 1 2 5 8."

Students are introduced to advanced GANs, including StyleGANs, and their applications.

"Working with Different GAN Models: You've gained experience with a variety of advanced GANs and learned how to use them to create images. You've also learned how to implement techniques associated with state-of-the-art GANs, like StyleGANs 1 2 5 8."

Students learn to apply GANs to solve problems in various domains.

"Applying GANs to Real-World Problems: You've learned how to apply GANs to solve problems in areas like computer vision, multimedia, 3D models, and natural language processing. You've also learned how to use GANs for data augmentation and privacy preservation 1 2 5 8."

Students gain a comprehensive understanding of GANs and their applications.

"You've gained a deep understanding of the fundamental components and applications of GANs."

"Understanding of GANs: You've gained a deep understanding of the fundamental components and applications of GANs. This includes knowing how GANs work, their architecture, and the roles of the generator and discriminator networks 1 2 5 8."

Students learn to build, implement, and train GANs using PyTorch.

"Building GANs: You've learned how to build and implement multiple GAN architectures using PyTorch. This includes creating basic GANs, advanced Deep Convolutional GANs (DCGANs), and conditional GANs capable of generating examples from determined categories 1 2 6 8."

"Training GANs: You've learned how to train GANs, including how to deal with common challenges like imbalances between the generator and discriminator, unstable training, and mode collapse. You've also learned how to apply loss functions, such as the W-Loss function, to solve the vanishing gradient problem 1 2 5 8."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Apply Generative Adversarial Networks (GANs) with these activities:

Peer Discussion: Unpaired Image-to-Image Translation

Show steps

Engage with peers to deepen your comprehension of unpaired image-to-image translation and the role of CycleGAN in this process.

Browse courses on CycleGAN

Show steps

Form a study group with fellow classmates
Discuss the key concepts of unpaired image-to-image translation
Explore the architecture and implementation of CycleGAN

Show all one activities

Career center

Learners who complete Apply Generative Adversarial Networks (GANs) will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting data to extract meaningful insights. The Apply Generative Adversarial Networks (GANs) course can help Data Scientists build a foundation in GANs, which are powerful tools for data augmentation and privacy preservation. By understanding the applications of GANs and leveraging the image-to-image translation framework, Data Scientists can enhance their data analysis and modeling capabilities.

See salaries and explore the career path for Data Scientist

Computer Vision Engineer

Computer Vision Engineers design, develop, and deploy computer vision systems. The Apply Generative Adversarial Networks (GANs) course can help Computer Vision Engineers build a foundation in GANs, which are a type of generative model that can be used to create new images. By understanding the applications of GANs and leveraging the image-to-image translation framework, Computer Vision Engineers can enhance their system development and deployment capabilities.

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Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. The Apply Generative Adversarial Networks (GANs) course can help Machine Learning Engineers build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Machine Learning Engineers can enhance their model development and deployment capabilities.

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Software Engineer

Software Engineers design, develop, and deploy software applications. The Apply Generative Adversarial Networks (GANs) course can help Software Engineers build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Software Engineers can enhance their application development and deployment capabilities.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts collect, analyze, and interpret data to extract meaningful insights. The Apply Generative Adversarial Networks (GANs) course can help Data Analysts build a foundation in GANs, which are powerful tools for data augmentation and privacy preservation. By understanding the applications of GANs and leveraging the image-to-image translation framework, Data Analysts can enhance their data analysis and modeling capabilities.

See salaries and explore the career path for Data Analyst

Research Scientist

Research Scientists conduct research to develop new technologies and products. The Apply Generative Adversarial Networks (GANs) course can help Research Scientists build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Research Scientists can enhance their research and development capabilities.

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Product Manager

Product Managers are responsible for the development and launch of new products. The Apply Generative Adversarial Networks (GANs) course can help Product Managers build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Product Managers can enhance their product development and launch capabilities.

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Business Analyst

Business Analysts analyze business processes to identify areas for improvement. The Apply Generative Adversarial Networks (GANs) course can help Business Analysts build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Business Analysts can enhance their process analysis and improvement capabilities.

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Project Manager

Project Managers plan, execute, and close projects. The Apply Generative Adversarial Networks (GANs) course can help Project Managers build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Project Managers can enhance their project planning, execution, and closing capabilities.

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Sales Engineer

Sales Engineers support sales teams by providing technical expertise. The Apply Generative Adversarial Networks (GANs) course can help Sales Engineers build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Sales Engineers can enhance their technical support and sales capabilities.

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Marketing Manager

Marketing Managers plan and execute marketing campaigns. The Apply Generative Adversarial Networks (GANs) course can help Marketing Managers build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Marketing Managers can enhance their campaign planning and execution capabilities.

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Financial Analyst

Financial Analysts analyze financial data to make investment recommendations. The Apply Generative Adversarial Networks (GANs) course can help Financial Analysts build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Financial Analysts can enhance their data analysis and investment recommendation capabilities.

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Human Resources Manager

Human Resources Managers plan and execute human resources strategies. The Apply Generative Adversarial Networks (GANs) course may be useful for Human Resources Managers who want to build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Human Resources Managers can enhance their strategy planning and execution capabilities.

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Operations Manager

Operations Managers plan and execute operations strategies. The Apply Generative Adversarial Networks (GANs) course may be useful for Operations Managers who want to build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Operations Managers can enhance their strategy planning and execution capabilities.

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Customer Success Manager

Customer Success Managers support customers to ensure they are successful with a product or service. The Apply Generative Adversarial Networks (GANs) course may be useful for Customer Success Managers who want to build a foundation in GANs, which are a type of generative model that can be used to create new data. By understanding the applications of GANs and leveraging the image-to-image translation framework, Customer Success Managers can enhance their support and success capabilities.

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