The recent explosion of interest in machine learning has resulted in a profusion of algorithms. It can be difficult to know which one is most suited to your problem.
Recognizing this challenge Microsoft have produced a machine learning algorithm cheat sheet. It’s designed to allow you to choose between the algorithms available in Microsoft’s Azure Machine Learning Studio, but, as many of the algorithms are generic, it’s applicable to other machine learning toolkits.
By following a path from your general task, and desirable features of the model, you end up at a suggested algorithm. For example, if you are looking to predict values and need accuracy and fast training, then a decision forest regression is suggested.
Of course, selection of an appropriate machine learning algorithm is a non-trivial task. A cheat-sheet is no replacement for a trained data scientist. And, the cheat sheet has obvious weaknesses. For example, a neural network regression is classified as an accurate approach to predicting values, but with a long training time. Given that, why would I ever pick a neural network over a decision forest when faced with a regression problem?!
However, if you are new to machine learning, and are bewildered by the choices, it’s a good place to start.