Generative Adversarial Networks and TF-GAN (ML Tech Talks)

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 → https://goo.gle/3AfOjf0
GANSynth project page → https://goo.gle/3xcm8vr
Batch equalization paper → https://goo.gle/2TgkudL
Superresolution colab → https://goo.gle/3y5xbqi
Image-to-image translation colab → https://goo.gle/3hmwYrZ
CycleGAN colab → https://goo.gle/3dwKyrG
Inception Score implementation → https://goo.gle/3ydL322
Frechet Inception Distance implementation → https://goo.gle/2UMTfYo
Self-Attention GAN implementation → https://goo.gle/3627o6q
TF-GAN examples → https://goo.gle/3w3xvEE

Catch more ML Tech Talks → http://goo.gle/ml-tech-talks
Subscribe to TensorFlow → https://goo.gle/TensorFlow

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