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| - | ====== EECS 6327 Probabilistic Models & Machine Learning (Fall 2016) ====== | + | ====== EECS 6327 Probabilistic Models & Machine Learning (Winter 2018) ====== |
| ===== Description | ===== Description | ||
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| * Generative Models (2) - graphical models, directed vs. indirected graphical models, exact inference, approximate inference (loopy belief propagation, | * Generative Models (2) - graphical models, directed vs. indirected graphical models, exact inference, approximate inference (loopy belief propagation, | ||
| * Discriminative Models (1) - linear discriminant, | * Discriminative Models (1) - linear discriminant, | ||
| - | * Discriminative Models (2) - neural networks (NN), back-propagation, | + | * Discriminative Models (2) - neural networks (NN), back-propagation, |
| * Advanced models: hidden Markov model (HMM), | * Advanced models: hidden Markov model (HMM), | ||
| - | * Advanced topics: | + | * Advanced topics: |
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| ===== Lecture Times ===== | ===== Lecture Times ===== | ||
| - | * Section A: Wednesdays | + | * Section A: Tuesdays |
| ===== Lecturer ===== | ===== Lecturer ===== | ||
| * Prof. [[http:// | * Prof. [[http:// | ||
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