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var page_no = getCurrentPageNumber(); | |
var macro_flag = false; | |
function wait(msecs) { | |
var start = new Date().getTime(); | |
var cur = start; | |
while (cur - start < msecs) { | |
cur = new Date().getTime(); | |
} | |
} |
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import numpy as np | |
import pandas as pd | |
from keras.models import Sequential | |
from keras.layers import Dense, LSTM, Dropout, Conv2D, Reshape, TimeDistributed, Flatten, Conv1D,ConvLSTM2D, MaxPooling1D | |
from keras.layers.core import Dense, Activation, Dropout | |
from sklearn.preprocessing import MinMaxScaler | |
from sklearn.metrics import mean_squared_error | |
import tensorflow as tf | |
import matplotlib.pyplot as plt |
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https://drive.google.com/open?id=1tTsEtlIJl69OiYKqwYxp0aviE69hJq32 |
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Installing, this may take a few minutes... | |
Please create a default UNIX user account. The username does not need to match your Windows username. | |
For more information visit: https://aka.ms/wslusers | |
Enter new UNIX username: layy | |
Enter new UNIX password: | |
Retype new UNIX password: | |
passwd: password updated successfully | |
Installation successful! | |
To run a command as administrator (user "root"), use "sudo <command>". | |
See "man sudo_root" for details. |
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import numpy as np | |
import pandas as pd | |
from keras.models import Sequential | |
from keras.layers import Dense, LSTM, Dropout, Conv2D, Reshape, TimeDistributed, Flatten, Conv1D,ConvLSTM2D, MaxPooling1D | |
from keras.layers.core import Dense, Activation, Dropout | |
from sklearn.preprocessing import MinMaxScaler, StandardScaler | |
from sklearn.metrics import mean_squared_error | |
import tensorflow as tf | |
import matplotlib.pyplot as plt |
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def create_dataset(signal_data, look_back=1): | |
dataX, dataY = [], [] | |
for i in range(len(signal_data) - look_back): | |
dataX.append(signal_data[i:(i + look_back), :]) | |
dataY.append(signal_data[i + look_back, -1]) | |
return np.array(dataX), np.array(dataY) | |
look_back = 20 |
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import numpy as np | |
import pandas as pd | |
from keras.models import Sequential | |
from keras.layers import Dense, LSTM, Dropout, Conv2D, Reshape, TimeDistributed, Flatten, Conv1D,ConvLSTM2D, MaxPooling1D | |
from keras.layers.core import Dense, Activation, Dropout | |
from sklearn.preprocessing import MinMaxScaler | |
from sklearn.metrics import mean_squared_error | |
import tensorflow as tf | |
import matplotlib.pyplot as plt |
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