| Session Name: | Math for Game Programmers: The Math of Deep Learning |
| Speaker(s): | Alex Champandard |
| Company Name(s): | creative.ai |
| Track / Format: | Programming |
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| Overview: | Neural Networks are back and this time they work! There are many applications for games, in particular generating unique textures or finding patterns in replay data. Recent progress with deep architectures can be attributed in part to the underlying technology, progressing at a fast pace since the late 2000s. This session will look at the mathematics behind deep neural networks, starting with the most commonly used functions and representations, then looking at gradient-based optimization, finally tying in the most recent research. |
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