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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.
Autor Zhang, Zhang (Intel) Última actualización 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

 

Autor JON J K. (Intel) Última actualización 03/07/2019 - 10:17
Article

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

Autor JON J K. (Intel) Última actualización 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.
Autor Andres Rodriguez (Intel) Última actualización 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.
Autor Gennady F. (Blackbelt) Última actualización 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.
Autor Sunny G. (Intel) Última actualización 08/05/2018 - 10:50
Article

面向英特尔® 架构优化的 Caffe*:使用现代代码技巧

This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
Autor Última actualización 06/07/2019 - 16:40
Article

安装英特尔® Theano*软件优化包和支持工具

Theano* is a Python* library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays. Theano can be installed and used with several combinations of development tools and libraries on a variety of platforms. This tutorial provides one such recipe describing steps to build and install Intel-optimized Theano with Intel®...
Autor Sunny G. (Intel) Última actualización 08/05/2018 - 10:50
Article

借助针对英特尔® 架构优化的 Caffe* 管理深度学习网络

如何面向英特尔® 架构优化 Caffe*,训练深度网络模型及部署网络。
Autor Andres Rodriguez (Intel) Última actualización 11/03/2019 - 13:17
Article

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...
Autor Última actualización 11/03/2019 - 13:17