In this session of Machine Learning Tech Talks, Research Engineer Joel Shor will discuss a very cool development and technique in machine learning called Generative Adversarial Networks (GANs) and a library that offers open source to help make training and evaluating GANs easier. Chapters: 0:00 - Introduction 1:29 - Demos from Google 11:42 - What is a GAN? 27:14 - What are GANs good for? 41:59 - Deep dive: Metrics 54:05 - Deep dive: Self-attention GAN 57:47 - How to get started Resources: Boundless video → GANSynth project page → Batch equalization paper → Superresolution colab → Image-to-image translation colab → CycleGAN colab → Inception Score implementation → Frechet Inception Distance implementation → Self-Attention GAN implementation → TF-GAN examples →
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