Skema for forelæsningerne
Forelæsninger og øvelser er i moduler på en halv dag for hvert emne (8-12 og 13-17) og finder sted på DTU, Lyngby Campus. Vi arrangerer frokost fra 12-13, men studerende skal betale deres egen frokost. Skemaet herunder kan blive underlagt mindre ændringer - indholdet vil være: cross-validation, model selection, bias-variance trade-off, over and under fitting, sparse regression, sparse classification, logistic regression, linear discriminant analysis, clustering, classification and regression trees, multiple hypothesis testing, principal component analysis, sparse principal component analysis, support vector machines, neural networks, self-organizing maps, random forests, boosting, non-negative matrix factorization, independent component analysis, archetypical analysis, og sparse coding.
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Module
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Date
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Subjects
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Lecturer
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Litterature
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1
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24/8
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Introduction to computational data analysis [OLS, Ridge]
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Line
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ESL Chapters 1, 2, 3.1, 3.2, 3.4.1, 4.1
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2
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24/8
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Model selection [CV, Bootstrap, Cp, AIC, BIC, ROC]
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Line
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ESL Chapter 7 and 9.2.5. You may safely skip sections 7.8 and 7.9
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3
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25/8
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Sparse regression [Lasso, elastic net]
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Line
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ESL Chapters 3.3, 3.4, 18.1, and 18.7
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4
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25/8
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Sparse classifiers [LDA, Logistic regression]
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Line
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ESL Chapters 4.3, 4.4, 18.2, 18.3, 18.4, 5.1, and 5.2
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5
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26/8
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Nonlinear learners [Support vector machines, CART and KNN]
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Line
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ESL Chapters 4.5, 4.4, 5.1, 5.2, 9.2 and 13.3
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6
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26/8
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Ensemble methods [Bagging, random forest, boosting]
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Line
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ESL Chapter 8.7, 9.2, 10.1 and 15
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7
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27/8
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Subspace methods [PCA, SPCA, PLS, CCA, PCR]
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Line
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ESL Chapters 14.5.1, 14.5.5 and 3.5
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8
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27/8
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Unsupervised decompositions [ICA, NMF, AA, Sparse Coding]
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Line
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ESL Chapters 14.6 - 14.10,[Sparse Coding, Nature]
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9
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28/8
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Cluster analysis [Hierarchical, K-means, GMM, Gap-Statistic]
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Line
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ESL Chapter 14.3
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10
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28/8
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Artificial Neural Networks and Self Organizing Maps
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Line
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11.1-11.5 and 14.5
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Eksamen
Den studerende skal deltage i kurset og aflevere en lille rapport om et eller flere af kursets emner relateret til de studerendes egen forskning eller arbejde. Karaktererne er bestået / ikke bestået. Deadline for rapporten er en måned fra det sidste forelæsning (dvs. slutningen af september).