| require "ikku" | |
| reviewer = Ikku::Reviewer.new | |
| sourceTextFileName = '../data/wiki.txt' | |
| outputTextFileName = 'math.txt' | |
| outputTextFile = File.open(outputTextFileName,'w') | |
| begin | |
| File.open(sourceTextFileName) do |file| | |
| file.each_line do |line| |
#Ingestibles
| 指標A | 指標B | correlation | 捕捉 |
|---|---|---|---|
| Hot Dog Eating Contentの優勝者のホットドッグ消費量 | NY timesベストセラーリストででフィクション作品が1位になった数 | 91.5 | |
| チーズの消費量 | ベッドのシーツのもつれ事故 | 94.7 | |
| マーガリンの消費量 | メイン州の離婚率 | 98.9 | |
| チキンの消費量 | 紙とボード製品の消費量 | 99.6 | |
| マクドナルドの顧客満足度 | 食道を詰まらせる死亡事故件数 | 85.6 | |
| 茶の消費量 | 芝刈り機の誤操作での死亡人数 | 93 | |
| 牛肉の消費量 | 落雷での死亡数 | 87 |
| <!DOCTYPE html> | |
| <!--[if lt IE 7]><html class="no-js lt-ie9 lt-ie8 lt-ie7" lang="ja"><![endif]--> | |
| <!--[if IE 7]><html class="no-js lt-ie9 lt-ie8" lang="ja"><![endif]--> | |
| <!--[if IE 8]><html class="no-js lt-ie9" lang="ja"><![endif]--> | |
| <!--[if gt IE 8]><!--><html class="no-js" lang="ja"><!--<![endif]--> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1"> | |
| <meta name="viewport" content="width=device-width,initial-scale=1,user-scalable=no"> |
| import numpy | |
| import matplotlib.pyplot as plt | |
| import chainer | |
| from chainer import cuda | |
| import chainer.functions as F | |
| import chainer.links as L | |
| from chainer import optimizers | |
| from chainer import cuda, Function, gradient_check, Variable, optimizers, serializers, utils | |
| from chainer import Link, Chain, ChainList |
| # -*- coding: utf-8 -*- | |
| import numpy | |
| import matplotlib.pyplot as plt | |
| def predict(w, x): | |
| output = numpy.dot(w, x) | |
| if output >= 0: |
using paper.js blendemode "xor"
A Pen by naoyashiga on CodePen.
| <html> | |
| <head> | |
| <style> | |
| * { | |
| margin: 0; | |
| padding: 0; | |
| } | |
| </style> | |
| <script src="http://cdnjs.cloudflare.com/ajax/libs/p5.js/0.4.22/p5.js"></script> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.4.23/addons/p5.sound.min.js"></script> |
| # -*- coding: utf-8 -*- | |
| import input_data | |
| import tensorflow as tf | |
| # prameters | |
| learning_rate = 0.01 | |
| training_epochs = 1000 | |
| def main(): |
| var gulp = require('gulp'), | |
| sass = require('gulp-ruby-sass') | |
| notify = require("gulp-notify") | |
| webserver = require('gulp-webserver'); | |
| gulp.task('server', function() { | |
| gulp.src('./') | |
| .pipe(webserver({ |
| class BaseParticleWithVector implements BaseParticleWithVectorInterface { | |
| PVector location; | |
| PVector velocity; | |
| float scalarVelocity; | |
| float r; | |
| BaseParticleWithVector() { | |
| location = new PVector(random(width), random(height)); | |
| velocity = new PVector(0, 0); |