| 周次 |
課程內容 |
課程影音 |
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Introduction to Machine Learning |
線上觀看
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The Growth of a Data Scientist |
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Machine Learning: Overview (1/2) |
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Machine Learning: Overview (2/2) |
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Mathematical Background (1/2) |
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Mathematical Background (2/2) |
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Three Fundamental Learning Algorithms - Naive Bayes Algorithm |
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Three Fundamental Learning Algorithms - k-Nearest Neighbor Algorithm |
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Three Fundamental Learning Algorithms - Perceptron Algorithm (1/2) |
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Three Fundamental Learning Algorithms - Perceptron Algorithm (2/2) |
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Evaluating the Learning Models |
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Learning Theory (1/2) |
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Learning Theory (2/2) |
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Optimization (1/5) |
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Optimization (2/5) |
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Optimization (3/5) |
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Optimization (4/5) |
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Optimization (5/5) |
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Support Vector Machine(SVM) (1/6) |
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Support Vector Machine(SVM) (2/6) |
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Support Vector Machine(SVM) (3/6) |
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Support Vector Machine(SVM) (4/6) |
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Support Vector Machine(SVM) (5/6) |
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Support Vector Machine(SVM) (6/6) |
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Sequential Minimal Optimization (SMO) (1/2) |
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Sequential Minimal Optimization (SMO) (2/2) |
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Anomaly Detection via Online Over Sampling Principal Component Analysis (1/2) |
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Anomaly Detection via Online Over Sampling Principal Component Analysis (2/2) |
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Nonlinear Dimension Reduction with Kernel Sliced Inverse Regression |
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Clustering and EM Algorithm (1/4) |
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Clustering and EM Algorithm (2/4) |
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Clustering and EM Algorithm (3/4) |
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Clustering and EM Algorithm (4/4) |
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Online Nonlinear Support Vector Machine for Large-Scale Classification (1/2) |
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Online Nonlinear Support Vector Machine for Large-Scale Classification (2/2) |
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