Article

如何安装 Python* 版英特尔® 数据分析加速库(英特尔® 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 13/07/2018 - 14:32
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Intel® AI Academy: The Future of AI. For All.

Autor Jaclyn J. (Intel) Última actualización 24/01/2018 - 15:35
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Top Ten Intel Software Developer Stories December

This month we introduce our newest VR newsletter deVR Beat; link to the keynotes from the Intel® HPC Developer Conference,meet the winners of the Intel® Modern Code Challenge and more.
Autor Carman, Vicky (Intel) Última actualización 05/02/2019 - 10:48
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Top Ten Intel Software Developer Stories March

Create a safe VR social environment and learn more about object detection specifically for drone videos.
Autor Karissa Pagliero (Intel) Última actualización 12/12/2018 - 18:00
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AI DevCamp:Chicago

I write this as an observer of something I had yet to witness.

Autor Karl Fezer (Intel) Última actualización 14/08/2018 - 16:20
Article

Get Started with Intel® SDK for OpenCL™ Applications 2019 on Windows* OS

1. Overview

Autor MICHAEL C. (Intel) Última actualización 13/12/2018 - 13:56
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Accelerate Deep Image Matting Algorithm Inference on Intel Platforms

Introduction
Autor Manuj Sabharwal (Intel) Última actualización 04/01/2019 - 17:00
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 27/08/2019 - 14:30
Article

Scale-Up Implementation of a Transportation Network Using Ant Colony Optimization (ACO)

In this article an OpenMP* based implementation of the Ant Colony Optimization algorithm was analyzed for bottlenecks with Intel® VTune™ Amplifier XE 2016 together with improvements using hybrid MPI-OpenMP and Intel® Threading Building Blocks were introduced to achieve efficient scaling across a four-socket Intel® Xeon® processor E7-8890 v4 processor-based system.
Autor Sunny G. (Intel) Última actualización 15/10/2019 - 16:40