Advanced Data Analytics Using Python_ With Machine Learning, Deep Learning and NLP Examples ( 2023)

Chapter 5
Deep Learning and Neural Networks
except Exception as e:
print (str(e))
print ('Training duration (s) : ', time.time() - global_
start_time)
return model, y_test, predicted
if __name__ == '__main__':
path_to_dataset = '20170301_ltp.csv'
data = read_data(path_to_dataset)
error = []
diff_predicted = []
err_predicted = []
print len(data)
for i in range(0,len(data)-1000,89):
d = data[i:i+1000]
model, y_test, predicted = run_network(None,d, False)
if i > 11 and len(error) >= 1000:
model,err_test, err_predicted =
run_network(None,error, True)
error = error[90:]
d1 = data[i:i+1001]
diff = [0]*1000
for k in range(1000):
diff[k] = d1[k+1] - d1[k]
model,diff_test, diff_predicted =
run_network(None,diff, True)
print i,len(d), len(y_test)
y_test *= result_std
predicted *= result_std
y_test += result_mean
predicted += result_mean
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