Description
Build GANs and Diffusion Models with TensorFlow and PyTorch Course If you’re looking for a crash course in generative modeling, this is the course for you. Generative Adversarial Networks (GANs) and propagation models are some of the most important components of machine learning infrastructure. Join instructor Janani Ravi to learn more about how to get started building GANs with dense neural networks and deep convolutional networks. Javani will show you the basics of training a deep convolutional GAN on multi-channel images. Along the way, he’ll give you tips on how to get GANs up and running with TensorFlow and propagation models with PyTorch.
What you will learn in the course “Build GANs and Diffusion Models with TensorFlow and PyTorch”
- Introduction to GANs and diffusion models
- Overview of the architecture of a GAN
- Common problems of GANs
- Get started with Google Colab
- Loading the MNIST mode dataset
- Training an adversarial network generator
- Image generation with GAN
- Deep Convolutional GANs
- Grayscale images: Training a deep convolutional GAN
- And…
Course details
- Editor: LinkedIn
- Lecturer: Janani Ravi
- Training level: beginner to advanced
- Course time: 2 hours and 22 minutes
Course headings
Pictures from the course “Build GANs and Diffusion Models with TensorFlow and PyTorch”.
Sample video of the course
installation Guide
After extracting, you can watch it with your favorite player.
English subtitles
Quality: 720p
Download link
free download software
Size
1.5GB