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.
Learn how to install and use BigDL for training and testing some of the commonly used deep neural network models on Apache Spark.
This article presents a simple step-by-step way to install the neon framework in Ubuntu* 14.04 using the Anaconda* Python* distribution. It also guides users through what to do if errors are encountered during the installation process.
Automated Installation of BigDL Using Deploy to Azure*
The information provided in this paper describes how to build and install TensorFlow* Serving, a high-performance serving system for machine learning models designed for production environments.
In this paper, you will learn how to train and save a TensorFlow* model, build a TensorFlow model server, and test the server using a client application.
This tutorial describes one way to implement a CNN (convolutional neural network) for single image super-resolution optimized on Intel® architecture from the
This article explores what happens when Intel solutions support functional and logic programming languages that are regularly used for Artificial Intelligence (AI) and proposes a Prolog interpreter recompilation using Intel® C++ Compiler and libraries in order to evaluate their contribution to logic based AI.