Variational autoencoders and GANs have been two of the most interesting recent developments in deep learning and machine learning. GAN stands for generative adversarial network, where two neural networks compete with each other. Unsupervised learning means you’re not trying to map input data to targets, you’re just trying to learn the structure of that input data. In this course, you’ll learn the structure of data in order to produce more stuff that resembles the original data.
- Access 41 lectures & 5.5 hours of content 24/7
- Incorporate ideas from Bayesian Machine Learning, Reinforcement Learning, & Game Theory
- Discuss variational autoencoder architecture
- Discover GAN basics
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