Concept of BeginneR Session

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Tsukuba.R #1 Kickoff meeting Concept of "BeginneR Session" @kilometer00 2018.10.07 at Tsukuba – Cases Report –

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Who！？

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Who！？名前：三村 @kilometer00 職業：ポスドク (こうがくはくし) 専⾨：⾏動神経科学脳イメージング医療システム⼯学 R歴： ~ 10年ぐらい流⾏: イタ飯

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BeginneR Session in

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Configuration of 1. Beginner Session 2. Advanced Session 3. LT Session Basic knowledge, Global usage, Tutorial Application case, Developed own pkgs 5min short talk (lightning talk)

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Evolution of Tokyo.R Jan 27, 2010

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Evolution of Tokyo.R Jan 27, 2010 Beginners Session

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BeginneR

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Before After BeginneR Session BeginneR BeginneR

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BeginneR Advanced Hoxo_m If I have seen further it is by standing on the sholders of Giants. -- Sir Isaac Newton, 1676

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BeginneR Advanced * Landscape form the sholders of Giants * Philosophy of the climbing wall structure * Climbing techniques

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* Landscape form the sholders of Giants

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* Landscape form the sholders of Giants Advanced Session Application case, Developed own pkgs

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Beginner Session Basic knowledge, Global usage, Tutorial * Concept of the wall structure * Climbing techniques 3 1

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... * Climbing techniques

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... Perm Crimp Jug * Climbing techniques Diagonal move

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... Perm Crimp Jug * Techniques Diagonal move How How How How

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... Perm Crimp Jug * Techniques Diagonal move Why? Why? Why? Why? Why? Why? Why? Why? Why? How How How How * Concept Why? Why? Why? Why? Why? Why? Why?

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BeginneR Session in

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67th Tokyo.R at Otto Japan Inc. @kilometer Beginner’s Session 2 -- data manipulation --

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ブール演算⼦ Boolean Algebra A == B A != B A | B A & B A %in% B # equal to # not equal to # or # and # is A in B?

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George Boole 1815 - 1864 A Class-Room Introduction to Logic https://niyamaklogic.wordpress.com/c ategory/laws-of-thoughts/ Mathematician Philosopher &

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1JQFBMHFCSB X %>% f X %>% f(y) X %>% f %>% g X %>% f(y, .) f(X) f(X, y) g(f(X)) f(y, X) %>% {magrittr} 「dplyr再⼊⾨（基本編）」yutanihilation https://speakerdeck.com/yutannihilation/dplyrzai-ru-men-ji-ben-bian

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{magrittr} # こう書きますか？ 536&*/ dat1 <- f1(dat0, var1-1, var1-2) dat2 <- f2(dat1, var2) dat3 <- f3(dat2, var3) dat4 <- f4(var4-1, dat3, var4-2) dat5 <- f5(dat4, var5) dat6 <- f6(dat5, var6) 536&065 5IJOLJOH 3FBEJOH 1JQFBMHFCSB %>%

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{magrittr} # こうやって書く事もできます。 dat <- dat0 %>% f1(var1-1, var1-2) %>% f2(var2) %>% f3(var3) %>% f4(var4-1, ., var4-2) %>% f5(var5) %>% f6(var6) */ 065 1JQFBMHFCSB %>%

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{magrittr} dat <- iris %>% .[, 1:3] %>% prcomp iris %>% .[, 1:3] %>% prcomp -> dat “Passive” writing “Active” writing BはAがFされたもの AをFするとBになる 1JQFBMHFCSB %>%

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69th Tokyo.R @kilometer BeginneR Session 1 -- Data Import / Export -- 2018.04.21 at Roppongi

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Input Output Do NOT start from here Whatever … 1 2 3

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70th Tokyo.R @kilometer BeginneR Session 1 -- Bayesian Modeling -- 2018.06.09 at Microsoft Co.

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What is modeling?

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What is modeling? ℎ f X ℎℎ Truth Knowledge Narrow sense Broad sense

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likelihood prior posterior ≅ ) ∗ () likelihood | <(=|>)∗<(>|?) | <(@|?) <(=|>) prior distribution posterior distribution predictive distribution data () (|) Truth Information Criterion in Bayesian modeling ebidence CD (| = −H(=) + CD (| = − H(?) Free energy Generalization error ≈ ≈ = − log ≔ self-information

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Language Thought Natural Programing

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Think Write Programing Read

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