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Optimize Linear Regression Model with Intel® DAAL
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.Intel® Math Kernel Library for Deep Learning Networks: Part 1–Overview and Installation
Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.Intel® Math Kernel Library for Deep Neural Networks: Part 2 – Code Build and Walkthrough
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.BigDL – Scale-out Deep Learning on Apache Spark* Cluster
Learn how to install and use BigDL for training and testing some of the commonly used deep neural network models on Apache Spark.How to Install the neon™ Framework on Ubuntu*
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.Deploying BigDL on Microsoft’s Azure* Data Science Virtual Machine
Automated Installation of BigDL Using Deploy to Azure*Build and Install TensorFlow* Serving on Intel® Architecture
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.Train a TensorFlow* Model on Intel® Architecture
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.An Example of a Convolutional Neural Network for Image Super-Resolution—Tutorial
This tutorial describes one way to implement a CNN (convolutional neural network) for single image super-resolution optimized on Intel® architecture from the
Building and Probing Prolog* with Intel® Architecture
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.- 1
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