Generate Synthetic Images with DCGANs in Keras
Understand Deep Convolutional Generative Adversarial Networks (DCGANs and GANs)
Design and train DCGANs using the Keras API in Python
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. In our GAN setup, we want to be able to sample from a complex, high-dimensional training distribution of the Fashion MNIST images. However, there is no direct way to sample from this distribution. The solution is to sample from a simpler distribution, such as Gaussian noise. We want the model to use the power of neural networks to learn a transformation from the simple distribution directly to the training distribution that we care about. The GAN consists of two adversarial players: a discriminator and a generator. We’re going to train the two players jointly in a minimax game theoretic formulation. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
您要培养的技能
分步进行学习
在与您的工作区一起在分屏中播放的视频中，您的授课教师将指导您完成每个步骤：
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 DCGAN
指导项目工作原理
您的工作空间就是浏览器中的云桌面，无需下载
在分屏视频中，您的授课教师会为您提供分步指导
常见问题
常见问题
如果我购买指导项目，会得到什么？
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指导项目的讲师是谁？
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指导项目不支持旁听。
我需要具备多少经验才能做这个指导项目？
您可在页面顶部点按此指导项目的经验级别，查看任何知识先决条件。对于指导项目的每个级别，您的讲师会逐步为您提供指导。
我能直接通过 Web 浏览器来完成此指导项目，而不必安装特殊软件吗？
是，您可以在浏览器的云桌面中获得完成指导项目所需的一切。
指导项目的学习体验如何？
您可以直接在浏览器中于分屏环境下完成任务，以此从做中学。在屏幕的左侧，您将在工作空间中完成任务。在屏幕的右侧，您将看到有讲师逐步指导您完成项目。
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