Фильтры

Article

OpenCL 2.0 中的 GPU-Quicksort: 嵌套并行性和工作组扫描函数

简介
Автор: Robert I. (Intel) Последнее обновление: 31.05.2019 - 14:20
Article

How to Install the Python* Version of Intel® Data Analytics Acceleration Library (Intel® DAAL) in Linux*

The Intel® Data Analytics Acceleration Library (Intel® DAAL) 1, 2 is a software solution for data analytics. It provides building blocks for data preprocessing, transformation, modeling, predicting, and so on.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 05.07.2019 - 19:05
Блоги

Announcing the Intel® Distribution for Python* Beta

The Beta for Intel® Distribution for Python* 2017 has been available for 1 month and I wanted to share some of our experiences.

Автор: Robert C. (Intel) Последнее обновление: 31.12.2018 - 16:12
Article

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.
Автор: Sunny G. (Intel) Последнее обновление: 08.05.2018 - 10:50
Видео

Webinar: Deep Learning 101

Deep neural networks are capable of amazing levels of representation power resulting in state-of-the-art accuracy in areas such as computer vision, speech recognition, natural language processing,

Автор: Andres Rodriguez (Intel) Последнее обновление: 24.10.2018 - 15:36
Блоги

SHEPHERD: Just when I thought I was out... they pull me back in

Don't get me wrong, I was a quite willing participant with all of this. 

Автор: Последнее обновление: 10.07.2018 - 08:08
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®...
Автор: Sunny G. (Intel) Последнее обновление: 08.05.2018 - 10:50
Article

Benefits of Intel® Optimized Caffe* in comparison with BVLC Caffe*

Overview
Автор: JON J K. (Intel) Последнее обновление: 30.05.2018 - 07:00
Article

腾讯* 在基于英特尔® 至强® 处理器的游戏内购买推荐系统中使用机器学习

To enhance the online gaming user experience, Tencent uses an in-game purchase recommendation system employing the machine learning method to help users decide what equipment they would want to buy within their games. Tencent machine learning engine uses DGEMM6 extensively in its module to compute the coefficients for the logistic regression machine learning algorithm.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 12.12.2018 - 18:00
Видео

网络研讨会:深度学习 101

深度神经网络具备出色的高级表达功能,并在诸多领域展示了一流的准确性,如计算机视觉、语音识别、自然语言处理以及各种数据分析领域。 深度网络需要训练大量的计算。 英特尔正在优化常见的框架,如 Caffe*、TensorFlow* 和 Theano* 等,以显著提升性能,缩短单个节点的训练总时间。 英特尔还在增强上述框架的多节点分布式训练功能,以在多个节点间分享计算要求,进一步缩短训练时间。

Автор: IDZSupport K. Последнее обновление: 17.01.2019 - 02:17