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Using Intel Data Analytics Acceleration Library on Apache Spark*

Apache Spark* (http://spark.apache.org/) is a fast and general engine for large-scale data processing.

Authored by Zhang, Zhang (Intel) Last updated on 03/11/2019 - 13:17
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.
Authored by Nguyen, Khang T (Intel) Last updated on 07/05/2019 - 19:05
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.
Authored by Sunny G. (Intel) Last updated on 05/08/2018 - 10:50
Article
Article

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...
Authored by Gennady F. (Blackbelt) Last updated on 03/11/2019 - 13:17
Article

Improving the Performance of Principal Component Analysis with Intel® Data Analytics Acceleration Library

This article discusses an unsupervised machine-learning algorithm called principal component analysis (PCA) that can be used to simplify the data. It also describes how Intel® Data Analytics Acceleration Library (Intel® DAAL) helps optimize this algorithm to improve the performance when running it on systems equipped with Intel® Xeon® processors.
Authored by Nguyen, Khang T (Intel) Last updated on 07/05/2019 - 14:57
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.
Authored by Meghana R. (Intel) Last updated on 01/24/2018 - 15:35
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®...
Authored by Sunny G. (Intel) Last updated on 05/08/2018 - 10:50
Article

英特尔® 至强融核™ 处理器针对深度学习提供了出色的性能 - 正在迅速完善性能

Baidu’s recently announced deep learning benchmark, DeepBench, documents performance for the lowest-level compute and communication primitives for deep learning (DL) applications. The goal is to provide a standard benchmark to evaluate different hardware platforms using the vendor’s DL libraries.
Authored by Andres Rodriguez (Intel) Last updated on 01/24/2018 - 15:35
Article

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

Overview
Authored by JON J K. (Intel) Last updated on 05/30/2018 - 07:00