julia 100 exercises #juliatokyo
Post on 27-Aug-2014
1.886 Views
Preview:
DESCRIPTION
TRANSCRIPT
- Julia 100 #JuliaTokyo Michiaki ARIGA(@chezou) JuliaTokyo #1 @ BrainPad 2014/07/05
- Michiaki ARIGA (@chezou / github:chezou) Software Engineer at Cookpad Inc. Interest / kawasaki.rb / Machine Learning Casual Talks
- http://wp.me/pvR30-iT
- Julia Julia 100 Julia
- http://www.slideshare.net/chezou/ruby-28923469
- http://wp.me/pvR30-r0
- Gady D3.js
- http://www.slideshare.net/chezou/hajipata-julia
- http://wp.me/pvR30-sG
- Julia100
- Julia 100 https://github.com/chezou/julia-100-exercises
- Julia 100 https://github.com/chezou/julia-100-exercises Julia version of 100 numpy exercises https://github.com/rougier/numpy-100 ! nbviewer http://nbviewer.ipython.org/github/chezou/julia-100- exercises/blob/master/julia-100-exercises.ipynb ! http://wp.me/pvR30-tN
- + Z = np.zeros((5,5)) Z += np.arange(5) (zeros(Int64,5,5) .+ [0:4])' [y for x in 1:5, y in 0:4] `.+`
- Package Z = np.ones(10) I = np.random.randint(0,len(Z),20) Z += np.bincount(I, minlength=len(Z)) using StatsBase Z = ones(10) I = rand(0:length(Z), 20) Z += counts(I, 1:length(Z))
- 1,2,3,4,5 6,,,7,8 ,,9,10,11 using DataFrames readtable("missing.dat") Z = np.genfromtxt("missing.dat", delimiter=",") NADataArrays
- Z = np.zeros((8,8),dtype=int) Z[1::2,::2] = 1 Z[::2,1::2] = 1 Z = zeros(Int64,8,8) Z[1:2:end, 2:2:end] = 1 Z[2:2:end, 1:2:end] = 1
- [julia-user]
- Z = np.zeros((8,8),dtype=int) Z[1::2,::2] = 1 Z[::2,1::2] = 1 print Z Z = zeros(Int64,8,8) Z[1:2:end, 2:2:end] = 1 Z[2:2:end, 1:2:end] = 1 Z [(i+j)%2 for i=1:8, j=1:8] || 0.0417 sec 2.83e-6 sec
- Are they on Julia way?
- Julia
- (using google) StatsBase.jl, DataFrame.jl githubissue / Mailing List MATLAB / NumPy John myles white
- http://julia.readthedocs.org/en/latest/manual/
- http://statsbasejl.readthedocs.org/en/latest/
- http://www.mathworks.co.jp/jp/help/matlab/index.html
- http://mathesaurus.sourceforge.net/matlab-numpy.html
- http://stackoverow.com/questions/21890893/reading-csv-in-julia-is-slow- compared-to-python/21910850#21910850
- http://stackoverow.com/questions/21890893/reading-csv-in-julia-is-slow- compared-to-python/21910850#21910850
- NumPy, MATLAB Julia Python reject,
- Python
- MATLAB Julia
- Julia
- Julia T
- Pull-Req https://github.com/chezou/julia-100-exercises
top related