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Article

Intel C and C++ Compilers: Features and Supported Platforms

Intel® C++ Compiler Features Supported in Different Products
作者: Jennifer J. (Intel) 最后更新时间: 2017/03/27 - 15:20
Article

Intel® XDK FAQs - General

Provides frequently asked questions (FAQs) related to developing apps with the Intel® XDK, such as how to get started as a new user, installing more than one version of Intel XDK, signing an app and updating or uninstalling Intel XDK. It also covers questions related to the built-in Brackets editor, differences between mobile platforms, specifying app settings, and other topics.
作者: Anusha M. (Intel) 最后更新时间: 2017/03/27 - 14:38
Forum topic

build with Scons

Hi,

I am trying to build a C++ code, which includes daal.h, with using Scons. I use the following Sconstruct script to run:

env = Environment(

作者: Farzaneh Taslimi 最后更新时间: 2017/03/27 - 15:36
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Intel® Distribution for Python* | Overview

作者: 管理 最后更新时间: 2017/03/27 - 14:16
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Intel® Math Kernel Library (Intel® MKL)

Intel® Math Kernel Library (Intel® MKL) accelerates math processing routines that increase application performance and reduce development time.
作者: Martin, Kay 最后更新时间: 2017/03/27 - 14:15
Article

Introducing DNN primitives in Intel® Math Kernel Library

    Deep Neural Networks (DNNs) are on the cutting edge of the Machine Learning domain.

作者: Vadim Pirogov (Intel) 最后更新时间: 2017/03/27 - 14:14
Article

Training and Deploying Deep Learning Networks with Caffe* Optimized for Intel® Architecture

Caffe* is a deep learning framework developed by the Berkeley Vision and Learning Center (BVLC). Caffe optimized for Intel architecture is currently integrated with the latest release of Intel® Math Kernel Library (Intel® MKL) 2017 optimized for Advanced Vector Extensions (AVX)-2 and AVX-512 instructions which are supported in Intel® Xeon® and Intel® Xeon Phi™ processors (among others). This...
作者: Andres R. (Intel) 最后更新时间: 2017/03/27 - 14:11
视频

What is Intel® Optimized Caffe*

Caffe* is a deep learning framework that is useful for convolutional and fully connected networks, and recently recurrent neural networks were added.

作者: Gerald M. (Intel) 最后更新时间: 2017/03/27 - 14:09
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Digging Deeper | IoT Developer Journey

Get advanced guidance from Intel’s experts for creating IoT prototypes, adding sensors, and connecting to the cloud.
作者: 管理 最后更新时间: 2017/03/27 - 14:08
Article

Case Study – Using the Intel® Deep Learning SDK for Training Image Recognition Models

In this case study, we explore LeNet*,one of the prominent image recognition topologies for handwritten digit recognition, and show how the training tool can be used to visually set up, tune, and train the Mixed National Institute of Standards and Technology (MNIST) dataset on Caffe* optimized for Intel® architecture. Data scientists are the intended audience.
作者: Meghana R. (Intel) 最后更新时间: 2017/03/27 - 14:07
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