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课程:机器人深度学习 | 英特尔® 人工智能开发人员计划

Autor David C. (Intel) Última actualización 16/08/2019 - 15:41
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Curso: Compreensão aprofundada sobre Robótica | Programa para desenvolvedores de IA da Intel®

Aprenda os fundamentos do uso de algoritmos de aprendizado profundo em várias cargas de trabalho de robótica.
Autor David C. (Intel) Última actualización 16/08/2019 - 15:45

使用英特尔® SSSE3 指令集在本地语音识别中加速 DNN 算法

The main algorithm of speech recognition has changed to DNN (Deep Neural Network). Without internet, the speech recognition service in your mobile devices nearly useless, very few times it can listen to what you said and work.With support for the SSSE3 instruction set on Intel’s CPU, we could easy run a DNN based speech recognition application without the internet. Adding direct SSSE3 support...
Autor Última actualización 26/03/2019 - 16:08

基于英特尔® 至强 E5 系列处理器的单节点 Caffe 评分和训练

As Deep Neural Network (DNN) applications grow in importance in various areas including internet search engines and medical imaging, Intel teams are working on software solutions to accelerate these workloads that will become available in future versions of Intel® Math Kernel Library (Intel® MKL) and Intel® Data Analytics Acceleration Library (Intel® DAAL). This technical preview demonstrates...
Autor Gennady F. (Blackbelt) Última actualización 11/03/2019 - 13:17

R 语言中的OpenBLAS*和英特尔® 数学核心函数库的性能比较

Today, scientific and business industries collect large amounts of data, analyze them, and make decisions based on the outcome of the analysis. This paper compares the performance of Basic Linear Algebra Subprograms (BLAS), libraries OpenBLAS, and the Intel® Math Kernel Library (Intel® MKL).
Autor Nguyen, Khang T (Intel) Última actualización 06/07/2019 - 16:30

利用英特尔® 数据分析加速库提高 Python* 语言中朴素贝叶斯算法的性能

This article discusses machine learning and describes a machine learning method/algorithm called Naïve Bayes (NB) [2]. It also describes how to use Intel® Data Analytics Acceleration Library (Intel® DAAL) [3] to improve the performance of an NB algorithm.
Autor Nguyen, Khang T (Intel) Última actualización 06/07/2019 - 16:30

方案:基于英特尔® 至强融核™ 处理器 x 200 的面向深度学习优化的 Caffe*

The computer learning code Caffe* has been optimized for Intel® Xeon Phi™ processors. This article provides detailed instructions on how to compile and run this Caffe* optimized for Intel® architecture to obtain the best performance on Intel Xeon Phi processors.
Autor Vamsi Sripathi (Intel) Última actualización 11/03/2019 - 13:17

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

BigDL:一种面向 Apache Spark* 的分布式深度学习库

深度学习作为分布式机器学习的主要框架,将其添加至颇为常用的 Spark 框架具有重要意义,有助于 Spark 开发人员在单个框架内处理各种数据分析任务—包括数据处理、交互式查询和数据流处理。BigDL 提供三个重要特性,分别是丰富的深度学习支持、较高的单节点至强性能以及利用 spark 架构实现高效的横向扩展。
Autor Última actualización 11/03/2019 - 13:17

BigDL:一种面向 Apache Spark 的分布式深度学习库

BigDL is a distributed deep learning library for Apache Spark*; with BigDL, users can write their deep learning applications as standard Spark programs, which can directly run on top of existing Sp

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