Neural network topologies are especially useful for big data analytics, machine learning, and predictive modeling. Traditional scripting languages, however, present certain difficulties for developers who want to leverage multithreaded processing and put neural networks to work addressing their business challenges.

This white paper explains why neural networks are uniquely suited to analytics workloads and explores the features and benefits of Intel’s Math Kernel Library (MKL) for optimizing code in the parallel-processing age.