Forecasting

When you’re working with time series data, naturally things are going to point towards forecasting. And two of the most reliable classical tools for this are the ARIMA and SARIMA models. To be honest I was quite confused when I first learnt about these a year ago but they do make a ton of intuitive sense once you understand them on a deeper level. The names are similar, and so is their underlying logic, but there is a key difference that more or less decides which one you will pick in what scenario. ...

Deep Learning Gets the Spotlight, But Time Series Still Solves Real Problems In the machine learning landscape today, deep learning models - transformers, LSTMs, and other neural networks steal the show. They’re impressive, powerful, celebrated and make you feel smart too when you use them. However, when it comes to forecasting business metrics like sales, demand, or inventory, deep learning isn’t always the answer. Traditional time series models, especially ARIMA (AutoRegressive Integrated Moving Average) and its seasonal extension SARIMA, are some of the most effective and interpretable methods for forecasting structured temporal data. ...