10 - 3 - Gradient of Logistic Regression Error (15-38)
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9 - 4 - Linear Regression for Binary Classification (11-23)
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11 - 3 - Multiclass via Logistic Regression (14-18)
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10 - 2 - Logistic Regression Error (15-58)
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10 - 4 - Gradient Descent (19-18)(1)
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8 - 3 - Algorithmic Error Measure (13-46)
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9 - 1 - Linear Regression Problem (10-08)
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9 - 2 - Linear Regression Algorithm (20-03)
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15 - 1 - Model Selection Problem (16-00)
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11 - 2 - Stochastic Gradient Descent (11-39)
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29 谱聚类1
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25 spectral clustering
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15 - 4 - V-Fold Cross Validation (10-41)
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15 主坐标分析
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4 - 2 - Probability to the Rescue (11-33)
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13 Jacobian
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15 - 3 - Leave-One-Out Cross Validation (16-06)
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14 - 2 - Weight Decay Regularization (24-08)
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13 - 4 - Dealing with Overfitting (10-49)
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28 Fisher判别分析
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14 主元分析
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7 - 1 - Definition of VC Dimension (13-10)
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32 Computational Methods2
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6 条件期望
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5 - 2 - Effective Number of Lines (15-26)
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14 - 1 - Regularized Hypothesis Set (19-16)
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1 - 1 - Course Introduction (10-58)(1)
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13 - 1 - What is Overfitting- (10-45)
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11 - 4 - Multiclass via Binary Classification (11-35)
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18 最大似然估计方法
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37 Naive Bayes方法
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36 Linear classification2
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41 Boosting1
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31 Computational Methods1
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34 Kernel FDA
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6 - 4 - A Pictorial Proof (16-01)
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12 - 4 - Structured Hypothesis Sets (09-36)
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1 - 5 - Machine Learning and Other Fields (10-21)(1)
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8 - 1 - Noise and Probabilistic Target (17-01)
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12 - 3 - Price of Nonlinear Transform (15-37)
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13 核主元分析