Everyone loves neural networks. Until they start criticising your code, and your worth as a person…

When you are presented with a new time series forecasting problem, there are many things to consider.

The choice that you make directly impacts each step of the project from the design of a test harness to evaluate forecast models to the fundamental difficulty of the forecast problem that you are working on.

It is possible to very quickly narrow down the options by working through a series of questions about your time series forecasting problem. By considering a few themes and questions within each theme, you narrow down the type of problem, test harness, and even choice of algorithms for your project.

In this post, you will discover a framework that you can use to quickly understand and frame your time series forecasting problem.

To deal with variable solar and wind power, the startup Energy Vault is coming out of stealth mode to offer alternatives to lithium-ion batteries.