Description: This article introduces SymPy, a computer algebra system (CAS) for the Python programming language.

Description: An exploration of moving predictive modeling capabilities in R to real time operations.

Description: This article discusses how to handle semisupervised data. This type of data might have a large number of observations, yet a small number of labels.

Description: This article shows how to use a RBF Neural network to predict if a breast tumor is malignant. The network is trained using a genetic algorithm that uses C# multi-threading.

Description: Neural networks have fallen only to rise again twice. The latest incarnation borrows much from the past but adds elements to support deep learning. This article demonstrates the state of the art in deep neural network programming.

Description: Agent based modeling is a technique that can be used to predict complex interactions between individuals in an artificial environment. This article provides an introduction to Repast Py.

Description: The author presents autoencoders in a clear manner and then goes on to show an intriguing application where an autoencoder can alert us to events out of the ordinary.

Description: A look into how machine learning models implement classification and regression at a deeper level. Covers topics such as multi-regression, softmax, and ROC charts.

Description: Introduction to PMML and how to use of it in the R programming language. PMML is an interchange format for predictive models.

Description: Feature article providing a brief introduction to Cython.