Understanding Deepfakes with Keras
154 個評分

7,027 人已註冊
Implement a Deep Convolutional Generative Adversarial Network (DCGAN).
Train a DCGAN to synthesize realistic looking images.
154 個評分
7,027 人已註冊
Implement a Deep Convolutional Generative Adversarial Network (DCGAN).
Train a DCGAN to synthesize realistic looking images.
In this 2-hour long project-based course, you will learn to implement DCGAN or Deep Convolutional Generative Adversarial Network, and you will train the network to generate realistic looking synthesized images. The term Deepfake is typically associated with synthetic data generated by Neural Networks which is similar to real-world, observed data - often with synthesized images, videos or audio. Through this hands-on project, we will go through the details of how such a network is structured, trained, and will ultimately generate synthetic images similar to hand-written digit 0 from the MNIST dataset. Since this is a practical, project-based course, you will need to have a theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like Gradient Descent. We will focus on the practical aspect of implementing and training DCGAN, but not too much on the theoretical aspect. You will also need some prior experience with Python programming. 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 Tensorflow 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
deepfakes
GAN
Machine Learning
keras
在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:
Introduction
Importing and Plotting the Data
Discriminator
Generator
Generative Adversarial Network
Training the GAN
Final Results
您的工作空間就是瀏覽器中的雲桌面,無需下載
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由 DN 提供
2020年10月17日Its really helpful to start from here, I got some insights about how to proceed further.
由 TA 提供
2020年4月26日The project is good enough to give you a start with DCGANs.
由 BJ 提供
2020年4月17日Overall good course, but it need to improve online cloud platform.
由 AK 提供
2020年4月25日Very good course and way of explaining stuff. Technically from the scratch. Maybe inclusion of explanation of why the selected layers are selected on the first place.
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