Train MLP Neural Network on time series data?
So I posted this same question on machine learning mastery post about removing trends and seasonality difference transform for time series data. And Jason Brownlee responded to my questions:

Yes, you can use MLP, CNN and LSTM. It requires first converting the
data to a supervised learning problem using a sliding window:

https://machinelearningmastery.com/time-series-forecasting-supervised-learning/

Then evaluating models in a way that respects the temporal ordering of
obs, called walk-forward validation:

https://machinelearningmastery.com/backtest-machine-learning-models-time-series-forecasting/

You can see tens of tutorials and my book on this here:

https://machinelearningmastery.com/start-here/#deep_learning_time_series
MY REPLY TO THIS POST
Ben February 12, 2021 at 8:09 am #

Cool thanks for all the info. So if I used multivariate sliding window
for MLP NN, is Ok when training the model that shuffle_data == True?
or should I not shuffle training data…? Thanks so much!

Jason's REPLY TO MY QUESTION ABOVE
Jason Brownlee February 12, 2021 at 1:36 pm #

Yes, as long as all data in the training dataset is in the past
compared to the test set.