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@naoyashiga
naoyashiga / k_largest_elements_indices.py
Last active Apr 28, 2017
値が大きい上位K件の配列インデックスを取得
View k_largest_elements_indices.py
#探す対象リスト:my_arrayはnumpy
#例:上位3件
K = 3
# ソートはされていない上位k件のインデックス
unsorted_max_indices = np.argpartition(-my_array, K)[:K]
# 上位k件の値
y = my_array[unsorted_max_indices]
View autoencoder_mnist.py
# -*- coding: utf-8 -*-
# Inspired
# [TensorFlow-Examples/autoencoder.py at master · aymericdamien/TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/autoencoder.py)
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data", one_hot=True)
@naoyashiga
naoyashiga / faceDetect.py
Created Jan 22, 2017
python2.7,opencvで顔認識
View faceDetect.py
import cv2
from os import path
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
cascades_dir = path.normpath(path.join(cv2.__file__, '..', '..', '..', '..', 'share', 'OpenCV', 'haarcascades'))
cascade_f = cv2.CascadeClassifier(path.join(cascades_dir, 'haarcascade_frontalface_alt2.xml'))
def faceDetect(filePath):
@naoyashiga
naoyashiga / index.js
Created Jan 1, 2017
Facebook Messenger Bot, aws lambdaでおうむ返しbot
View index.js
const request = require('request');
const PAGE_ACCESS_TOKEN = "";
var options = {
hostname: "graph.facebook.com",
path: "/v2.6/me/messages?access_token=" + PAGE_ACCESS_TOKEN,
method: 'POST',
headers: {
'Content-Type': 'application/json'
@naoyashiga
naoyashiga / writeIkku.rb
Last active Dec 27, 2016
一句(五七五)を抽出してテキストに書き出す
View writeIkku.rb
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|
@naoyashiga
naoyashiga / SpuriousCorrelations.md
Last active Oct 4, 2016
Spurious Correlations指標翻訳まとめ
View SpuriousCorrelations.md

#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||

View kiji.html
<!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">
View ir.py
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
@naoyashiga
naoyashiga / singlePerceptron.py
Last active May 2, 2016
単純パーセプトロンの実装
View singlePerceptron.py
# -*- coding: utf-8 -*-
import numpy
import matplotlib.pyplot as plt
def predict(w, x):
output = numpy.dot(w, x)
if output >= 0:
@naoyashiga
naoyashiga / index.html
Created Mar 20, 2016
p5.js sound test
View index.html
<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>
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