Generative Deep Learning by David Foster
With this practical book, machine-learning engineers and data scientists will discover 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.
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'.
| SKU | Unavailable |
| ISBN 13 | 9781492041948 |
| ISBN 10 | 1492041947 |
| Title | Generative Deep Learning |
| Author | David Foster |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | O'Reilly Media |
| Year published | 2019-07-31 |
| Number of pages | 350 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |