Generative Deep Learning – Review/Discussion

Machine Learning Tokyo
Machine Learning Tokyo
Public group

Online Event

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Join us for the online Review/Discussion session for Generative Deep Learning – Part I (by David Foster).

We will be covering the following topics in this session:

● Generative Adversarial Networks (GANs, WGANs, WGAN-GPs)

● Join Zoom Meeting

General Information:
Our Generative Deep Learning Sessions are dedicated to reading and discussing the book "Generative Deep Learning" by David Foster (O'Reilly). All sessions are led by Anugraha Sinha.

––– Session structure –––
● 1.5 silent reading もくもくかい
● 30 min discussion

To get the most out of the sessions make sure to get the book, prepare for the session chapters and read a bit ahead if possible. That will serve as a good basis for an interactive and productive discussion.

Join us on Slack for discussions #generativedeeplearning

●● Book Info ●●

Book : Generative Deep Learning
Author : David Foster
Publication : O'Reilly

The book can be purchased e.g. on Amazon

●● Part 1 - Introduction to Generative Deep Learning ●●

📌 Session # 1 (59 pages)
Chapter 1 : Generative Modeling
Chapter 2 : Deep Learning

📌 Session #2 (34 pages)
Chapter 3 : Variational Autoencoders

📌 Session #3 (30 pages)
Chapter 4 : Generative Adversarial Networks

●● Part 2 - Teaching Machines to Paint, Write, Compose and Play ●●

📌 Session #4 (31 pages)
Chapter 5 : Paint

📌 Session #5 (35 pages)
Chapter 6 : Write

📌 Session #6 (34 pages)
Chapter 7 : Compose

📌 Session #7 (34 pages)
Chapter 8 : Play

📌 Session #8 (30 pages)
Chapter 9 : The Future of Generative Modelling

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