Alexander Ihler

Clustering (4) Gaussian Mixture Models and EM

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Clustering (3) K-Means Clustering

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Clustering (2) Hierarchical Agglomerative Clustering

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Clustering (1) Basics

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Neural Networks (2) Backpropagation

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Neural Networks (1) Basics

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Support Vector Machines (3) Kernels

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Support Vector Machines (2) Dual & soft-margin forms

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Support Vector Machines (1) Linear SVMs, primal form

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VC Dimension

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Linear classifiers (2) Learning parameters

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Linear classifiers (1) Basics

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Linear regression (6) Regularization

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Linear regression (2) Gradient descent

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Linear regression (4) Nonlinear features

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Linear regression (5) Bias and variance

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Linear regression (3) Normal equations

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Linear regression (1) Basics

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Introduction (2) Data and Visualization

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Introduction (1) AI & Machine Learning

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Introduction (3) Supervised Learning

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Introduction (4) Complexity and Overfitting

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Bayes Classifiers (2) Naive Bayes

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Bayes Classifiers (1)

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Nearest Neighbor (1)

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Nearest neighbor (2) k-nearest neighbor

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Multivariate Gaussian distributions

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PCA, SVD

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Clustering

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Review Probability

Alexander Ihler