Generate Synthetic Images with DCGANs in Keras
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Understand Deep Convolutional Generative Adversarial Networks (DCGANs and GANs)
Design and train DCGANs using the Keras API in Python
7,568 人已注册
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.
Deep Learning
Machine Learning
Tensorflow
Computer Vision
keras
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
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
由 SB 提供
Sep 11, 2020Nice choice to start with the understanding of GANs.
由 ST 提供
Jul 20, 2020Excellent instructor. Dense with content and comments explaining bits of code.
由 AA 提供
Dec 20, 2020Quick and easy to follow, very informative as well!
由 DC 提供
Aug 19, 2021Very clear and concise instructions, providing enough detail and references for further study.
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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。
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,您将看到有授课教师逐步指导您完成项目。
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