hiropppe

## check_variance_to_identify_garbage_text.ipynb

      
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                hiropppe
                / check_variance_to_identify_garbage_text.ipynb
            
            
              Created
              December 25, 2020 17:50
            
              
                文字や単語の分散が悪戯テキストの検出に使えそうなサンプル
              
          
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## wv_cosine_similarity_matrix_for_small_data.ipynb

      
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                hiropppe
                / wv_cosine_similarity_matrix_for_small_data.ipynb
            
            
              Last active
              December 25, 2020 17:56
            
              
                Gensim で作成した小さめの wv からコサイン類似度行列の作り方
              
          
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## jawiki_interlink_probability.py
#!/usr/bin/env python
# -*- coding:utf8 -*-
from __future__ import division
from __future__ import unicode_literals

import codecs
import json
import multiprocessing
import re
import sys

## jawiki_extract_titles.py
#!/usr/bin/env python
# -*- coding:utf8 -*-
from __future__ import unicode_literals

import codecs
import gzip
import re
import sys
import unicodedata

## jawiki_extract_interlinks.py
#!/usr/bin/env python
# -*- coding:utf8 -*-
from __future__ import unicode_literals

import bz2
import codecs
import mwparserfromhell
import multiprocessing
import re
import sys

## pandas_apply_udf_sample.py
In [1]: import pandas as pd

In [2]: data = {'a': [0,1,2], 'b': [3,4,5]}
   ...: df = pd.DataFrame(data)
   ...: df
   ...:
Out[2]:
   a  b
0  0  3
1  1  4

## pandas_SQL_analytic_and_aggregate_functions_like_operation_sample.py
In [1]: import pandas as pd
   ...:
   ...: data = {'m': ['m1','m2','m2','m3','m3','m3','m4','m4','m4','m4'],
   ...:         'e': ['e1','e2','e3','e4','e5','e6','e7','e1','e2','e8'],
   ...:         'p': [0.9, 0.2, 0.8, 0.7, 0.1, 0.2, 0.3, 0.1, 0.2, 0.4]}
   ...: df = pd.DataFrame(data)
   ...: df
   ...:
Out[1]:
    e   m    p

## print_twogtp_winratio.py
from __future__ import division

import re
import sys

from collections import defaultdict

is_alternate_game = False
if len(sys.argv) > 1:
    is_alternate_game = sys.argv[1] in ('--alternate', '-a')

## DBPediaDockerfile
FROM ubuntu:16.04

RUN mkdir /root/_INSTALL

WORKDIR /root/_INSTALL

RUN sed -i.bak -e "s%http://archive.ubuntu.com/ubuntu/%http://ftp.jaist.ac.jp/pub/Linux/ubuntu/%g" /etc/apt/sources.list

ENV TZ Asia/Tokyo
RUN apt-get update \

## nvidia-docker2_g3.4xlarge_setup.txt
[2018.6.11]
3  sudo apt update
4  sudo apt upgrade
6  sudo apt install build-essential
11  wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.2.88-1_amd64.deb
12  sudo dpkg -i cuda-repo-ubuntu1604_9.2.88-1_amd64.deb
13  sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
14  sudo apt-get update
15  sudo apt-get install cuda
16  nvidia-smi
	#!/usr/bin/env python
	# -- coding:utf8 --
	from __future__ import division
	from __future__ import unicode_literals

	import codecs
	import json
	import multiprocessing
	import re
	import sys
	In [1]: import pandas as pd

	In [2]: data = {'a': [0,1,2], 'b': [3,4,5]}
	...: df = pd.DataFrame(data)
	...: df
	...:
	Out[2]:
	a b
	0 0 3
	1 1 4
	In [1]: import pandas as pd
	...:
	...: data = {'m': ['m1','m2','m2','m3','m3','m3','m4','m4','m4','m4'],
	...: 'e': ['e1','e2','e3','e4','e5','e6','e7','e1','e2','e8'],
	...: 'p': [0.9, 0.2, 0.8, 0.7, 0.1, 0.2, 0.3, 0.1, 0.2, 0.4]}
	...: df = pd.DataFrame(data)
	...: df
	...:
	Out[1]:
	e m p
	FROM ubuntu:16.04

	RUN mkdir /root/_INSTALL

	WORKDIR /root/_INSTALL

	RUN sed -i.bak -e "s%http://archive.ubuntu.com/ubuntu/%http://ftp.jaist.ac.jp/pub/Linux/ubuntu/%g" /etc/apt/sources.list

	ENV TZ Asia/Tokyo
	RUN apt-get update \
	[2018.6.11]
	3 sudo apt update
	4 sudo apt upgrade
	6 sudo apt install build-essential
	11 wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.2.88-1_amd64.deb
	12 sudo dpkg -i cuda-repo-ubuntu1604_9.2.88-1_amd64.deb
	13 sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
	14 sudo apt-get update
	15 sudo apt-get install cuda
	16 nvidia-smi