ARIMA (AutoRegressive Integrated Moving Average) is a time series forecasting method that combines autoregression, differencing, and moving averages.
Exponential Smoothing is a time series forecasting method that applies weighted averages of past observations with the weights decaying exponentially over time.
LSTM (Long Short-Term Memory) is a type of recurrent neural network (RNN) capable of learning long-term dependencies, useful for predicting time series data.