Generate Synthetic Images with DCGANs in Keras

Offered byCoursera

Generate Synthetic Images with DCGANs in Keras
at
Coursera
Overview

A comprehensive overview of Generate Synthetic Images with DCGANs

Duration	2 hours
Mode of learning	Online
Difficulty level	Advanced
Credential	Certificate

Generate Synthetic Images with DCGANs in Keras
at
Coursera
Highlights

Certificate of completion

Generate Synthetic Images with DCGANs in Keras
at
Coursera
Course details

Skills you will learn

Python Networking

What are the course deliverables?

Understand Deep Convolutional Generative Adversarial Networks (DCGANs and GANs)
Design and train DCGANs using the Keras API in Python

More about this course

In this hands-on project, you will learn about Generative Adversarial Networks (GANs) and you will build and train a Deep Convolutional GAN (DCGAN) with Keras to generate images of fashionable clothes. We will be using the Keras Sequential API with Tensorflow 2 as the backend

Generate Synthetic Images with DCGANs in Keras
at
Coursera
Curriculum

Project Overview and Import Libraries

Load and Preprocess the Data

Create Batches of Training Data

Build the Generator Network for DCGAN

Build the Discriminator Network for DCGAN

Compile the Deep Convolutional Generative Adversarial Network (DCGAN)

Define the Training Procedure

Train DCGAN

Generate Synthetic Images with DCGANs in Keras
at
Coursera
Faculty details

Snehan Kekre

Snehan Kekre is a Developer Advocate at Snowflake, where he specializes in the Streamlit open-source Python library. In the past, he has worked for Streamlit (pre-acquisition) as a Developer Advocate , and has authored and taught over 40+ guided projects on machine learning and data science at Coursera. He has also worked as a skills consultant at Coursera, and as content strategist at Rhyme.com.