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Article

Tencent* Uses Machine Learning for In-Game Purchase Recommendation System on Intel® Xeon® Processors

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: 09.05.2019 - 13:08
Видео

Remove Python* Performance Barriers for Machine Learning

Online content and service providers like Netflix and Amazon have popularized the use of recommendation platforms/engines, that predict a user’s preferences based on historical ratings, collective

Автор: админ Последнее обновление: 13.02.2018 - 09:24
Article

Introducing DNN primitives in Intel® Math Kernel Library

Please notes: Deep Neural Network(DNN) component in MKL is deprecated since intel® MKL ​2019 and will be removed in the next intel® MKL Release.

Автор: Vadim Pirogov (Intel) Последнее обновление: 21.03.2019 - 12:00
Видео

Intel® Developer Zone Update: October 2016

In this episode we are looking at topics from: The Internet of Things: Intel Joule Module, and the Ultimate Coder Challenge, Machine Learning: with Pradeep Dubey Intel Software Tools announcements:

Автор: админ Последнее обновление: 10.07.2018 - 08:08
Видео

Fast Deep Learning at Your Fingertips

The new Intel® Deep Learning SDK introduced by Nir Lotan from Intel's Advanced Analytics department. The talk was delivered at the Strata+Hadoop World Singapore, December 2016.

Автор: админ Последнее обновление: 24.01.2018 - 15:35
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.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 05.07.2019 - 14:57
Блоги

Top Intel® Software Innovators of 2016

The Intel® Software Innovator program has been very active for 2016 with growing support for developers in North America, Brazil, Europe, India, Asia Pacific, and China.

Автор: Warner, Elizabeth (Intel) Последнее обновление: 20.06.2019 - 10:40
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.
Автор: Meghana R. (Intel) Последнее обновление: 24.01.2018 - 15:35
Видео

Python* Programming for Machine Learning

This webinar covers the following topics:

Автор: David L. (Intel) Последнее обновление: 28.12.2016 - 14:55
Article

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

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