Concept of BeginneR Session

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October 08, 2018
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Concept of BeginneR Session

Tukuba.R #1 にてお話しした内容です。

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October 08, 2018
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  1. Tsukuba.R #1 Kickoff meeting Concept of "BeginneR Session" @kilometer00 2018.10.07

    at Tsukuba – Cases Report –
  2. Who!?

  3. 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
  4. BeginneR Session in

  5. 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)
  6. Evolution of Tokyo.R Jan 27, 2010

  7. Evolution of Tokyo.R Jan 27, 2010 Beginners Session

  8. None
  9. BeginneR

  10. Before After BeginneR Session BeginneR BeginneR

  11. BeginneR Advanced Hoxo_m If I have seen further it is

    by standing on the sholders of Giants. -- Sir Isaac Newton, 1676
  12. BeginneR Advanced * Landscape form the sholders of Giants *

    Philosophy of the climbing wall structure * Climbing techniques
  13. * Landscape form the sholders of Giants

  14. * Landscape form the sholders of Giants Advanced Session Application

    case, Developed own pkgs
  15. Beginner Session Basic knowledge, Global usage, Tutorial * Concept of

    the wall structure * Climbing techniques 3 1
  16. ... * Climbing techniques

  17. ... Perm Crimp Jug * Climbing techniques Diagonal move

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

    How How
  19. ... 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?
  20. BeginneR Session in

  21. 67th Tokyo.R at Otto Japan Inc. @kilometer Beginner’s Session 2

    -- data manipulation --
  22. 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?
  23. George Boole 1815 - 1864 A Class-Room Introduction to Logic

    https://niyamaklogic.wordpress.com/c ategory/laws-of-thoughts/ Mathematician Philosopher &
  24. 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
  25. {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 %>%
  26. {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 %>%
  27. {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 %>%
  28. 69th Tokyo.R @kilometer BeginneR Session 1 -- Data Import /

    Export -- 2018.04.21 at Roppongi
  29. Input Output Do NOT start from here Whatever … 1

    2 3
  30. 70th Tokyo.R @kilometer BeginneR Session 1 -- Bayesian Modeling --

    2018.06.09 at Microsoft Co.
  31. What is modeling?

  32. What is modeling? ℎ f X ℎℎ Truth Knowledge Narrow

    sense Broad sense
  33. 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
  34. Language Thought Natural Programing

  35. Think Write Programing Read

  36. Beginner Session Basic knowledge, Global usage, Tutorial * Concept of

    the wall structure * Climbing techniques 3 1
  37. BeginneR Advanced Hoxo_m If I have seen further it is

    by standing on the sholders of Giants. -- Sir Isaac Newton, 1676
  38. “Life shrinks or expands to one’s courage.” -- Anaïs Nin,

    2000 http://theamericanreader.com
  39. Enjoy!! KMT©