DataScience

Explore a new framework that takes advantage of the highly-optimized Intel® Data Analytics Acceleration Library, complete with Java* code, and how to do k-means clustering using Harp-DAAL.

ANNs, CNNs, and DNNs—See why Intel® Math Kernel Library, Intel® Threading Building Blocks, and OpenMP* are instrumental in optimizing deep learning software.

One of the most common applications of outlier detection—credit card fraud—is presented to show how the Intel® Data Analytics Acceleration Library is used to achieve high performance and high accuracy.

Today’s business applications―such as analytics and deep learning—require extensive numerical computing. New enhancements to Java* enable optimized performance with the latest Intel® Xeon® processors.

Utilizing Intel® Advisor, part of Intel® Parallel Studio XE, is a powerful way to generate program statistics that can help you optimize your system with vectorized and threaded code.