Dexdev08
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| from keras.models import Sequential | |
| from keras.layers import Dense, Dropout, Activation | |
| from keras.optimizers import SGD | |
| import keras as keras | |
| import numpy as np | |
| x_train = np.random.random((1000,20)) | |
| y_train = keras.utils.np_utils.to_categorical(np.random.randint(10, size=(1000,1)), nb_classes=10) | |
| x_test = np.random.random((100,20)) | |
| y_test = keras.utils.np_utils.to_categorical(np.random.randint(10, size=(100,1)),nb_classes=10) |
Dexdev08
/ talk_python_similarities.py
Created
June 7, 2016 13:46
Copy from local Ipython Notebook to derive similarity scores of Talk Python Transcripts
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| import graphlab as gl | |
| import pandas | |
| import numpy as np | |
| import string | |
| import re | |
| import unicodedata | |
| import math | |
| # attempt to load text files | |
| import os | |
| files = os.listdir(os.getcwd()) |
Dexdev08
/ talk_python_similarities.csv
Created
June 5, 2016 14:36
Talk Python Cosine Similarity Scores
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| index | file2 | similarity | file1 | |
|---|---|---|---|---|
| 0 | 027.txt | 0.870699976021 | 001.txt | |
| 1 | 038.txt | 0.86203984054 | 001.txt | |
| 2 | 045.txt | 0.83739929573 | 001.txt | |
| 3 | 048.txt | 0.871940130115 | 001.txt | |
| 4 | 007.txt | 0.839339858402 | 001.txt | |
| 5 | 009.txt | 0.849677851534 | 001.txt | |
| 6 | 004.txt | 0.830406980293 | 001.txt | |
| 7 | 006.txt | 0.878178563493 | 001.txt | |
| 8 | 031.txt | 0.850476330623 | 001.txt |