SHOGUN is a machine learning toolbox whose focus is on large scale kernel methods and especially on Support Vector Machines (SVM). It provides a generic SVM object interfacing to several different SVM implementations, all making use of the same underlying, efficient kernel implementations. Apart from SVMs and regression, SHOGUN also features a number of linear methods like Linear Discriminant Analysis (LDA), Linear Programming Machine (LPM), (Kernel) Perceptrons, and algorithms to train hidden Markov models. SHOGUN can be used from within C++, Matlab, R, Octave, and Python.
QMentat helps you practice mental arithmetic. It uses arbitrary-length fixed point arithmetic, and can handle any size numbers, only limited by the size of your screen (and in the case of division with an integer result, the speed at which the number can be factored). It is also quite configurable, allowing you to tailor the questions to your needs.