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A Tutorial on the C++ API of Intel® Data Analytics Acceleration Library

Intel® DAAL is a part of Intel® Parallel Studio XE 2016, a developer toolkit for HPC and technical computing applications. Intel® DAAL is a powerful library for big data developers that turns large data clusters into meaningful information with advanced analytics algorithms. In this tutorial, we will see how to build and run Intel® DAAL C++ examples included in the package.
Authored by Zhang, Zhang (Intel) Last updated on 07/06/2019 - 10:53
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Tutorial for Intel® DAAL: Using Simple C++ Examples

System Environment

Intel® DAAL version : 2016 Gold Initial Release (w_daal_2016.0.110.exe)

OS : Windows* 8.1

IDE : Visual Studio 2013

 

Authored by JON J K. (Intel) Last updated on 07/03/2019 - 10:17
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Tutorial for Intel® DAAL : Using Simple Java* Examples

System Environment

Intel® DAAL version : 2016 Gold Initial Release (w_daal_2016.0.110.exe)

OS : Windows 8.1

Authored by JON J K. (Intel) Last updated on 07/06/2019 - 11:41
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Manage Deep Learning Networks with Caffe* Optimized for Intel® Architecture

How to optimize Caffe* for Intel® Architecture, train deep network models, and deploy networks.
Authored by Andres Rodriguez (Intel) Last updated on 03/11/2019 - 13:17
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How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL)

Intel® Data Analytics Acceleration Library (Intel® DAAL) is a software solution that offers building blocks covering all the stages of data analytics, from preprocessing to decision making. The beta version of Intel DAAL 2017 provides support for the Python* language.
Authored by Gennady F. (Blackbelt) Last updated on 10/08/2018 - 03:42
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Set Up Intel® Software Optimization for Theano* and Supporting Tools

Get recipes for installing development tools and libraries on various platforms for the Python library.
Authored by Sunny G. (Intel) Last updated on 05/08/2018 - 10:50
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BigDL: Distributed Deep Learning on Apache Spark*

As the leading framework for Distributed ML, the addition of deep learning to the super-popular Spark framework is important, because it allows Spark developers to perform a wide range of data analysis tasks—including data wrangling, interactive queries, and stream processing—within a single framework. Three important features offered by BigDL are rich deep learning support, High Single Node Xeon...
Authored by Last updated on 03/11/2019 - 13:17
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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.
Authored by Nguyen, Khang T (Intel) Last updated on 02/25/2019 - 11:43
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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.
Authored by Bryan B. (Intel) Last updated on 05/23/2018 - 11:00
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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.
Authored by Sunny G. (Intel) Last updated on 03/11/2019 - 13:17