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The asymptotic parameter regime that we'll be focusing on for the rest of this course. The time offsets for the various slides in this presentation are as follows: [00:00]: [cache] Cache Misses [02:14]: [cache] Virtual ... We talk about Universal Approximation by NNs, this motivates us to use Deep NNs for ML. We then formally define Deep NNs and ... We take a short detour to see an application of Stanford Winter Quarter 2016 class: CS231n: Convolutional Neural Networks for Visual Recognition. An example of what might go wrong if we try to do Assista a esta palestra em português em youtu.be/1dV61IMUwIc, graças ao lingopal.ai. Mira esta conferencia en español ... Hashing: load balancing, k-wise independence, chaining,
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