Forecasting Methods : Part I – Taposh Dutta-Roy – Medium

Recently, I was asked to teach a class on forecasting using Python. I thought my notes would be a good source of information for every one interested in this area and I might learn from my reader's feedback as well. In this part 1 of the article we will talk about basic forecasting methods -- Naive, Average, Moving Average and Weighted Average. In the next parts we will discuss measures of scoring, exponential smoothing techniques, Holt, Holt winters, ARIMA, ARMA and deep learning methods using LSTM. Incidentally Kaggle also released a competition on forecasting which plans to forecast for 145K time series.