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David Foster

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Generative Deep Learning

Generative modelling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavours such as painting, writing, and composing music. David Foster will show how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders, generative adversarial networks (GANs), encoder-decoder models, and world models. Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative.

David Foster is the co-founder of Applied Data Science, a data science consultancy delivering bespoke solutions for clients. He holds an MA in Mathematics from Trinity College, Cambridge, UK and an MSc in Operational Research from the University of Warwick. David has won several international machine learning competitions, including the Innocentive Predicting Product Purchase challenge and was awarded first prize for a visualisation that enables a pharmaceutical company in the US to optimize site selection for clinical trials. He is an active participant in the online data science community and has authored several successful blog posts on deep reinforcement learning including ‘How To Build Your Own AlphaZero AI’.


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