Ken Morishita mokemokechicken

## stat.js
// https://github.com/numpy/numpy/blob/master/numpy/random/mtrand/distributions.c
// https://github.com/numpy/numpy/blob/master/numpy/random/mtrand/randomkit.c

function DistributionSampling(seed) {
  // xorshift: https://sbfl.net/blog/2017/06/01/javascript-reproducible-random/
  var state = {
      x: 123456789,
      y: 362436069,
      z: 521288629,
      w: seed || 88675123,

## scatter_with_colors_and_legends.py
p_list = np.argmax(api.predict(dataset.x), axis=1)
color_master = sns.color_palette()
colors = [color_master[ptn] for ptn in p_list]
names = api.predict_names()

g = sns.JointGrid("x", "y", data=zz)
g = g.plot_joint(plt.scatter, c=colors, label=p_list)
g = g.plot_marginals(sns.distplot, kde=True)

bb = g.ax_joint.viewLim

## find_files_including_null_bytes.sh
sudo find /usr /lib /etc -type f -size +100  \( -exec grep -q -P "[^\0]" {} \; -o -print \) | head

## q.py
"""
問：

あなたは

1. この質問に「いいえ」と正しく答えるか
2. この質問に「はい」と間違って答えるか
3. 教師に１万円を支払うか

のいずれかですか？

## transfer_money.ipynb

      
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              July 11, 2017 07:24
            
          
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## keras_mnist_vat.py
# coding: utf8
"""
* VAT: https://arxiv.org/abs/1507.00677

# 参考にしたCode
Original: https://github.com/fchollet/keras/blob/master/examples/mnist_cnn.py
VAT: https://github.com/musyoku/vat/blob/master/vat.py

results example
---------------

## 2016-j1league-1st.csv

          
            away_score
            away_team
            date
            home_score
            home_team
            score
            visitors

            
              1
              名古屋
              02/27(土)
              0
              磐田
              0-1
              14333

            
              1
              川崎Ｆ
              02/27(土)
              0
              広島
              0-1
              18120

            
              1
              福岡
              02/27(土)
              2
              鳥栖
              2-1
              19762

            
              2
              浦和
              02/27(土)
              1
              柏
              1-2
              13416

            
              2
              新潟
              02/27(土)
              1
              湘南
              1-2
              14058

            
              2
              甲府
              02/27(土)
              0
              神戸
              0-2
              23862

            
              1
              仙台
              02/27(土)
              0
              横浜FM
              0-1
              24898

            
              1
              大宮
              02/27(土)
              0
              FC東京
              0-1
              25776

            
              1
              鹿島
              02/28(日)
              0
              Ｇ大阪
              0-1
              32463

## for_bayesian_opt_article.ipynb

      
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                mokemokechicken
                / for_bayesian_opt_article.ipynb
            
            
              Created
              September 2, 2016 03:21
            
              
                bayesian optimization sample
              
          
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## Dockerfile
From jupyter/datascience-notebook

RUN curl -k -L -O https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp34-none-linux_x86_64.whl && \
    mv tensorflow-0.7.1-cp34-none-linux_x86_64.whl tensorflow-0.7.1-cp35-none-linux_x86_64.whl
RUN pip install tensorflow-0.7.1-cp35-none-linux_x86_64.whl
RUN /bin/bash -c "source activate /opt/conda/envs/python2/ && pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl"

## Dockerfile-jupyter-tensorflow
From jupyter/datascience-notebook

RUN curl -k -L -O https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp34-none-linux_x86_64.whl && \
    mv tensorflow-0.7.1-cp34-none-linux_x86_64.whl tensorflow-0.7.1-cp35-none-linux_x86_64.whl
RUN pip install tensorflow-0.7.1-cp35-none-linux_x86_64.whl
RUN /bin/bash -c "source activate /opt/conda/envs/python2/ && pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl"
	// https://github.com/numpy/numpy/blob/master/numpy/random/mtrand/distributions.c
	// https://github.com/numpy/numpy/blob/master/numpy/random/mtrand/randomkit.c

	function DistributionSampling(seed) {
	// xorshift: https://sbfl.net/blog/2017/06/01/javascript-reproducible-random/
	var state = {
	x: 123456789,
	y: 362436069,
	z: 521288629,
	w: seed \|\| 88675123,
	p_list = np.argmax(api.predict(dataset.x), axis=1)
	color_master = sns.color_palette()
	colors = [color_master[ptn] for ptn in p_list]
	names = api.predict_names()

	g = sns.JointGrid("x", "y", data=zz)
	g = g.plot_joint(plt.scatter, c=colors, label=p_list)
	g = g.plot_marginals(sns.distplot, kde=True)

	bb = g.ax_joint.viewLim
	"""
	問：

	あなたは

	1. この質問に「いいえ」と正しく答えるか
	2. この質問に「はい」と間違って答えるか
	3. 教師に１万円を支払うか

	のいずれかですか？
	# coding: utf8
	"""
	* VAT: https://arxiv.org/abs/1507.00677

	# 参考にしたCode
	Original: https://github.com/fchollet/keras/blob/master/examples/mnist_cnn.py
	VAT: https://github.com/musyoku/vat/blob/master/vat.py

	results example
	---------------
away_score	away_team	date	home_score	home_team	score	visitors
1	名古屋	02/27(土)	0	磐田	0-1	14333
1	川崎Ｆ	02/27(土)	0	広島	0-1	18120
1	福岡	02/27(土)	2	鳥栖	2-1	19762
2	浦和	02/27(土)	1	柏	1-2	13416
2	新潟	02/27(土)	1	湘南	1-2	14058
2	甲府	02/27(土)	0	神戸	0-2	23862
1	仙台	02/27(土)	0	横浜FM	0-1	24898
1	大宮	02/27(土)	0	FC東京	0-1	25776
1	鹿島	02/28(日)	0	Ｇ大阪	0-1	32463
	From jupyter/datascience-notebook

	RUN curl -k -L -O https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp34-none-linux_x86_64.whl && \
	mv tensorflow-0.7.1-cp34-none-linux_x86_64.whl tensorflow-0.7.1-cp35-none-linux_x86_64.whl
	RUN pip install tensorflow-0.7.1-cp35-none-linux_x86_64.whl
	RUN /bin/bash -c "source activate /opt/conda/envs/python2/ && pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl"