DeepLearning.AI
Generative Deep Learning with TensorFlow
DeepLearning.AI

Generative Deep Learning with TensorFlow

This course is part of TensorFlow: Advanced Techniques Specialization

Taught in English

Some content may not be translated

Laurence Moroney
Eddy Shyu

Instructors: Laurence Moroney

16,553 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.9

(248 reviews)

Intermediate level

Recommended experience

16 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.9

(248 reviews)

Intermediate level

Recommended experience

16 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the TensorFlow: Advanced Techniques Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

This week, you will learn how to extract the content of an image (such as a swan), and the style of a painting (such as cubist, or impressionist), and combine the content and style into a new image. This is called neural style transfer, and you'll learn how to extract these kinds of features using transfer learning.

What's included

13 videos7 readings1 quiz1 programming assignment3 ungraded labs

This week, you’ll get an overview of AutoEncoders and how to build them with TensorFlow. You'll learn how to build a simple AutoEncoder on the familiar MNIST dataset, before diving into more complicated deep and convolutional architectures that you'll build on the Fashion MNIST dataset. You'll get to see the difference in results of the DNN and CNN AutoEncoder models, and then identify ways to denoise noisy images. You'll finish the week building a CNN AutoEncoder using TensorFlow to output a clean image from a noisy one!

What's included

6 videos1 reading1 quiz1 programming assignment5 ungraded labs

This week you will explore Variational AutoEncoders (VAEs) to generate entirely new data. In this week’s assignment, you will generate anime faces and compare them against reference images.

What's included

6 videos3 readings1 quiz1 programming assignment1 ungraded lab

This week, you’ll learn about GANs. You'll learn what they are, who invented them, their architecture and how they vary from VAEs. You'll get to see the function of the generator and the discriminator within the model, and the concept of 2 training phases and the role of introduced noise. Then you'll end the week building your own GAN that can generate faces! How cool is that!

What's included

7 videos10 readings1 quiz1 programming assignment3 ungraded labs

Instructors

Instructor ratings
4.9 (49 ratings)
Laurence Moroney
DeepLearning.AI
15 Courses481,323 learners

Offered by

DeepLearning.AI

Recommended if you're interested in Machine Learning

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4.9

248 reviews

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4

Reviewed on Apr 30, 2021

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Reviewed on Aug 18, 2022

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