How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls

There are several types of models that can be used for time-series forecasting. In this specific example, I used a Long short-term memory network, or in short LSTM Network, which is a special kind of neural network that make predictions according to the data of previous times. It is popular for language recognition, time series analysis and much more. However, in my experience, simpler types of models actually provide just as accurate predictions in many cases. Due to their sequential nature, TDNN's are implemented as a feedforward neural network instead of a recurrent neural network.