How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL) in Linux*The Intel® Data Analytics Acceleration Library (Intel® DAAL) 1, 2 is a software solution for data analytics. It provides building blocks for data preprocessing, transformation, modeling, predicting, and so on.
Improving the Performance of Principal Component Analysis with Intel® Data Analytics Acceleration LibraryThis article discusses an unsupervised machine-learning algorithm called principal component analysis (PCA) that can be used to simplify the data. It also describes how Intel® Data Analytics Acceleration Library (Intel® DAAL) helps optimize this algorithm to improve the performance when running it on systems equipped with Intel® Xeon® processors.
Intel® Distribution for Python 2017 Update 2 accelerates five key areas for impressive performance gains
Intel Corporation is pleased to announce the release of Intel® Distribution for Python* 2017 Update 2, which offers both performance improvements and new features.
This article describes a common type of regression analysis called linear regression and how the Intel® Data Analytics Acceleration Library helps optimize this algorithm on Intel® Xeon® processors.
Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.
Learn how to configure the Eclipse* IDE to build the C++ code sample, along with a code walkthrough based on the AlexNet deep learning topology for AI applications.
This article presents a performance test of Intel® tuning platform composed by Intel® processor, Intel® C++ Compiler XE and Intel® Math Kernel Library (Intel® MKL) applied to usual AI problems, with two existing approaches of artificial intelligence probed.
What we call deep learning is typically associated with servers, the cloud, or high-performance computing. We are witnessing a reshuffling of compute partitioning between cloud data centers and clients in favor of moving applications of deep learning models to the client.