The family of Auto Regressive Integrated Moving Average (ARIMA) models are worth mentioning because they are traditionally used in time series forecasting. While I'm obviously a big fan of deep neural networks (in fact I wrote a book about them), I suggest starting with ARIMA and progressing towards deep learning. In many cases, ARIMA will outperform the LSTM. This is especially true when data is sparse.
Start with the simplest model that could possibly work. Sometimes that will be a deep neural network, but often it will be something much simpler, such as a linear regression or an ARIMA model. The model's complexity should be justified by the lift it provides, and often simpler is better. While reiterated several ...
