Accelerate your machine learning: introducing mlpack 3.0

Popular libraries make up the backbone of data science: scikit-learn, TensorFlow, Caffe, and Keras are the standard Python choices. But these libraries don't tend to implement niche techniques (scikit-learn's policy actually states that they don't consider algorithms less than three years old or with less than 200 citations!), Enter mlpack: a flexible, fast machine learning library. It's written in C, with bindings to Python and command-line programs that can be used for simpler data science tasks. Because of its use of templates for configurability, it is easy to customize the specific behavior of algorithms without any runtime penalty.