Spam filtering, face recognition, recommendation engines -- when you have a large data set on which you’d like to perform predictive analysis or pattern recognition, machine learning is the way to go. This science, in which computers are trained to learn from, analyze, and act on data without being explicitly programmed, has surged in interest of late outside of its original cloister of academic and high-end programming circles.
This rise in popularity is due not only to hardware growing cheaper and more powerful, but also the proliferation of free software that makes machine learning easier to implement both on single machines and at scale. The diversity of machine learning libraries means there’s likely to be an option available regardless of what language or environment you prefer.
These 11 machine learning tools provide functionality for individual apps or whole frameworks, such as Hadoop. Some are more polyglot than others: Scikit, for instance, is exclusively for Python, while Shogun sports interfaces to many languages, from general-purpose to domain-specific.