Many sophisticated machine learning algorithms cannot process large amounts of data on a single node, but Parallel Machine Learning Toolbox (PML) can do so by distributing the computations. This distribution speeds up computations and expedites training by weeks, days, or even hours in an easy, reliable way. PML can run on a wide array of architectures including single-node, small clusters, grids, and BlueGene.