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Ml workshop jul2015_mm

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Mind map for the proposed machine learning workshop. Covers the core ideas to be covered in the workshop.

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Ml workshop jul2015_mm

  1. 1. Domain understanding. asymetric costs. evaluation. metrics Simple representations . ‘l Representing Linear and generalized l"1f°"'T‘a'5l°" linear models l l Complexl non-linear representations ‘ SVMs ‘ C Id Tree based models ‘ ore eas ‘ l 7 Name] netw°, }$ ‘ i . /’ I _ _ ' ~ 1. Cost functions and likelihoods T ' _ ~ — l'E_Cl"ne '-°“"_"{'E/ 2. Optimization and searching best fit parameters Deep '9 “"9 ’ ’ T 3. Regularizatlon and Ocaam's razor 4. Basics of Bayesian methodology 1. Model complexity. selection 2. Training time — 3. Cost of labelled data T"ade. °ff§ E 4. Feature interpretabllity 5. Output representation

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