Articles on Forecasting

In this post, I provide a walkthrough of using statistical tests (like the Dickey-Fuller test) to check stationary data while forecasting time series.

This post provides an introduction to forecasting time series using autoregression models. A walkthrough is provided along with sample code.

Do you need machine learning? Maybe. Maybe not. Everyone's talking about machine learning but its not the answer to every problem.

Forecasting with Random Forests is possible with the proper setup.

Guidance for non-technical people on how to ask the right questions to evaluate whether a machine learning model is good enough for the job.

In this article I look at stock market forecasting with prophet and compare a few errors measures to see how well prophet can forecast the market.

Prophet does a very good job of detecting trend changepoints. In this post, I provide an example where I look at the capabilities of Prophet.

This third installment of Forecasting time series data with prophet provides an example using holidays to try to improve the model.

In this article, I provide a few tips to make a bit more realistic and useful visualizations from Facebook's Prophet for forecasting time-series library.

Forecasting time-series data with Prophet. Prophet is a fairly new library for python and R to help with forecasting time-series data.