Deep Learning with PyTorch : Generative Adversarial Network (Guided Project)

About this course

Two-hour project-based course: implement a Deep Convolutional Generative Adversarial Network using PyTorch to generate handwritten digits; create a generator that learns to generate images that look real and a discriminator that learns to tell real images apart from fakes; setup Google Runtime, load the MNIST handwritten dataset, create discriminator and generator networks, loss function and optimizers, train the GAN; requires prior Python programming and basic PyTorch, plus theoretical knowledge of convolutional neural networks.

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Frequently Asked Questions

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This course is designed for learners at the Beginner level who want to advance their skills in Programming. It is suitable for students, working professionals and lifelong learners looking to gain practical expertise.

How long does this course take?

The estimated duration is 2 hours. Since the course is fully online, you can learn at your own pace and revisit the material as often as you need.

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