monisoi

import numpy as np
import tensorflow as tf

def tensorflow_FizzBuzz():
    NUM_DIGITS = 10
    
    def binary_encode(i, num_digits):
        return np.array([i >> d & 1 for d in range(num_digits)])
    
    def fizz_buzz_encode(i):

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require './jumanpp.rb'
# http://qiita.com/rtoya/items/33e5ac410704b70800b2 のruby用ラッパーコードを使用
# Open3.popen3('jumanpp') を　Open3.popen3('jumanpp -M') に変更
require 'pp'

file_name = './sample.txt'
imported_words = []

File.open(file_name) do |file|
  jumanpp = Jumanpp::Parser.new

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if __name__ == '__main__':
    from sklearn import datasets
    from sklearn.model_selection import train_test_split
    from random_forest import RandomForest

    iris = datasets.load_iris()
    X = iris.data
    y = iris.target

    X_train, X_test, y_train, y_test = train_test_split(

monisoi

import numpy as np
from node import _Node
from sklearn.base import ClassifierMixin


class DecisionTree(ClassifierMixin):
    def __init__(self):
        self._root = None

    def create_tree(self, X, y):

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# coding: utf-8
import numpy as np
from im2col import im2col

class Convolution:
    def __init__(self, W, b, stride=1, pad=0):
        self.W = W
        self.b = b
        self.stride = stride
        self.pad = pad

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import urllib.request
import sys
import os
import json


def download(import_file, number_of_files):
    f = open(import_file, 'r')
    json_data = json.load(f)
    images = json_data["images"]

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import urllib.request
import sys
import os
import json


def merge_by_image_id(import_file):
    merged_images = []
    f = open(import_file, 'r')
    json_data = json.load(f)

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