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- ---
- title : CoreML algorytms
- subtitle : From the beginings to the not
- author : metya
- job : Летняя Школа 2018, Deep Learning Workshop
- framework : io2012 # {io2012, html5slides, shower, dzslides, ...}
- highlighter : highlight.js # {highlight.js, prettify, highlight}
- hitheme : tomorrow #
- widgets : [mathjax] # {mathjax, quiz, bootstrap}
- mode : selfcontained # {standalone, draft}
- knit : slidify::knit2slides
- guthub :
- user: 'metya'
- repo: 'CoreML'
- ---
- # A few base algorythms and even farther
- ---
- # Regression
- - Linear regression ([объяснение на хабре](https://habr.com/company/ods/blog/323890/))
- - NonLinear Regression
- - Descision Trees
- - Autoregression (ARIMA, etc.)
-
- (множественные модели, многомерные модели, регрессионные остатки)
- ---
- # Classification
- - Logistic regression ([объяснение на хабре](https://habr.com/company/ods/blog/323890/))
- - Descision Trees ([объяснение на хабре](https://habr.com/company/ods/blog/322534/))
- - K Nearest Neighbours ([объяснение на хабре](https://habr.com/company/ods/blog/322534/))
- - Naive Bayes ([Wiki](https://ru.wikipedia.org/wiki/Наивный_байесовский_классификатор), [habr (свежак!)](https://habr.com/post/415963/))
- - Linear discriminant analysis (Fisher's)
- - Support Vector Machine ([хабр](https://habr.com/post/105220/))
- - Genetics Algorithms
- - Expectation-Maximization (EM) ([где то в интернете](https://basegroup.ru/community/articles/em))
- ---
- # Clusterization
- ([Николенко, слайды](https://logic.pdmi.ras.ru/~sergey/teaching/mlau12/10-clustem.pdf), [воронцов, лекция](http://www.ccas.ru/voron/download/Clustering.pdf))
- - K-means ([объяснение на хабре](https://habr.com/company/ods/blog/325654/))
- - DBSCAN ([хабр](https://habrahabr.ru/post/322034/))
- - Affinity Propagation ([habr](https://habr.com/post/321216/))
- - EM
- - Self-Organaized Maps aka Kohonen's networks ([все там же отличная статья!](https://habr.com/post/338868/))
- - Principal Component Analysis aka Понижение размерности ([объяснение на хабре](https://habr.com/company/ods/blog/325654/))
- - t-SNE
- ---
- # Many of them together
- - Bagging aka Bootstrap aggregation (Random Forest, etc.)
- ([объяснение на хабре](https://habr.com/company/ods/blog/324402/))
- - Boosting ([все там же](https://habr.com/company/ods/blog/327250/), [дьяконов](https://alexanderdyakonov.wordpress.com/2017/06/09/градиентный-бустинг/comment-page-1/), [чья то неплохая курсовая](http://www.machinelearning.ru/wiki/images/9/9a/fonarev.overview_of_boosting_methods.pdf))
- --- .middle
- # FIN!
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