Advanced Mathematics for AI

1.1-1. Data Representation

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2.1-2. Matrix Decomposition

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3.1-3. SVD Application

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4.1-4. NMF

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5.1-5. NMF Application

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6.2-1. Loss Function

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7.2-2. Optimization using GD

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8.2-3. Stochastic Gradient Descent

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9.2-4. Convex Function

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10.2-5. Convex Optimization

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11.3-1. Classification

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12.3-2. Maximal Margin Classifier

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13.3-3. Soft Margin Classifier

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14.3-4. Support Vector Machine

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15.3-5. Kernels

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16.4-1. Bayes' Theorem

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17.4-2. Bayesian Inference

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18.4-3. Bayesian Inference Example

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19.4-4. Bayesian Network

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20.4-5. Independence in Bayesian Networks

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