AI6 Cycle 1 Learning Materials
Stanford STAT385 Theories of Deep Learning
About the Stanford STAT385 Theories of Deep Learning category
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Lagrangian formulation of backpropagation
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Wiki: Lecture 2 – Overview of Deep Learning from a Practical Point of View
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Wiki: Discussion on STAT385 Lecture 1 Video and Readings
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Wiki: Lecture 10 – CNNs in view of Sparse Coding
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Wiki: Lecture 9 – What's Missing in Deep Learning
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Wiki: Lecture 8 – Topology and Geometry of Half-rectified Network Optimization
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Wiki: Lecture 7 – Understanding and Improving Deep Learning With Random Matrix Theory
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Wiki: Lecture 6 – Views of Deep Networks from Reproducing Kernel Hilbert Spaces
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Wiki: Lecture 5 – When Can Deep Networks Avoid the Curse of Dimensionality
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Wiki: Lecture 4 – Covnets from First Principles
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Wiki: Lecture 3 – Harmonic Analysis of Deep Convolutional Neural Networks
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