title: Future time series forecasting using LSTM
body: <p>I have written LSTM sequential code for forecasting time series as follows</p>
  
  <pre><code>model = Sequential()
  model.add(LSTM(4, input_shape=(1, no_input)))
  model.add(Dense(1))
  model.compile(loss='mean_squared_error', optimizer='adam')
  model.fit(trainX, trainY, epochs=20, batch_size=1, verbose=2)
  </code></pre>
  
  <p>Code works well with tested data. Now my question is, for example, If I want to forecast next 10K data, how can I do this? Where Just giving <code>number of data to be forecasted</code>, generates future values?</p>