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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.
Criado por Zhang, Zhang (Intel) Última atualização em 06/07/2019 - 10:53
Article

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

 

Criado por JON J K. (Intel) Última atualização em 03/07/2019 - 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

Criado por JON J K. (Intel) Última atualização em 06/07/2019 - 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.
Criado por Andres Rodriguez (Intel) Última atualização em 11/03/2019 - 13:17
Article

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.
Criado por Gennady F. (Blackbelt) Última atualização em 08/10/2018 - 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.
Criado por Sunny G. (Intel) Última atualização em 08/05/2018 - 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...
Criado por Última atualização em 11/03/2019 - 13:17
Article

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.
Criado por Nguyen, Khang T (Intel) Última atualização em 25/02/2019 - 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.
Criado por Bryan B. (Intel) Última atualização em 23/05/2018 - 11:00
Article

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.
Criado por Sunny G. (Intel) Última atualização em 11/03/2019 - 13:17