Understand the Math and Theory of GANs in ~ 10 minutes
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My name is Zak Jost and I'm currently working as a Research Scientist at Amazon Web Services in the Seattle area. The point of this channel is to help people like you level up their Machine Learning skills. The current focus of this channel will be on Video lectures and Hands-on Screencasts. For lecture material, the focus is on stripping away unnecessary formality and shining a light on the key points to build your intuition. However, I am a firm believer that we learn best by doing, so the screencasts will compliment the lectures by walking you through building things from scratch. Outside of YouTube, I also provide long-form blogs as a textual compliment. To keep up with the content announcements across all outlets, you can subscribe to my Email List using the link below.
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Video Description
Join my Foundations of GNNs online course (https://www.graphneuralnets.com)! This video takes a deep dive into the math of Generative Adversarial Networks. It explains the optimization function, steps through an algorithm for solving it, and theoretically proves that solving it leads to the perfect Generative model. Part 1 of this series gave a high-level overview of how GANs work: https://youtu.be/3z8VSpBL6Vg My blog series on GANs: https://blog.zakjost.com/tags/generative-adversarial-networks/ The original paper from Ian Goodfellow: http://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf Mailing List: https://blog.zakjost.com/subscribe Discord Server: https://discord.gg/xh2chKX Blog: https://blog.zakjost.com Patreon: https://www.patreon.com/welcomeaioverlords
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