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View webhookcare-demo.js
var webhookcare = require('webhookcare')('<API KEY>')
var payload = {
result: 'ok!'
}
webhookcare.send('http://user.com/callback') // Provide the url
.header('X-Secret-Header', 'a secret header') // Add headers (optional)
.json(payload) // provide a json payload (optional)
.end() // Send the request
View dispatch-demo.js
var dispatch = require('dispatch');
dispatch.url('https://user.com/callback')
.send({
json: 'payload'
})
.then((result) => {
// Webhook successfully delivered
}, (error) => {
// Retrying later
View sequence_pad.py
from keras.preprocessing import sequence
max_review_length = 1600
X_train = sequence.pad_sequences(X_train, maxlen=max_review_length)
X_test = sequence.pad_sequences(X_test, maxlen=max_review_length)
View keras_conv.py
from keras.layers import LSTM, Convolution1D, Flatten, Dropout, Dense
from keras.layers.embeddings import Embedding
from keras.models import Sequential
max_review_length = 1600
embedding_vecor_length = 300
model = Sequential()
model.add(Embedding(top_words, embedding_vecor_length, input_length=max_review_length))
model.add(Convolution1D(64, 3, border_mode='same'))
model.add(Convolution1D(32, 3, border_mode='same'))
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