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Using Intel® Data Analytics Acceleration Library to Improve the Performance of Naïve Bayes Algorithm in Python*

This article discusses machine learning and describes a machine learning method/algorithm called Naïve Bayes (NB) [2]. It also describes how to use Intel® Data Analytics Acceleration Library (Intel® DAAL) [3] to improve the performance of an NB algorithm.
Authored by Nguyen, Khang T (Intel) Last updated on 07/06/2019 - 16:40
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.

Authored by Vadim Pirogov (Intel) Last updated on 03/21/2019 - 12:00
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
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Intel® Media SDK & Intel® Media Server Studio Historical Release Notes

Release Notes of Intel® Media SDK include important information, such as system requirements, what's new, feature table and known issues since the previous release.

Authored by Liu, Mark (Intel) Last updated on 07/03/2019 - 20:07
Article

Intel® Math Kernel Library Improved Small Matrix Performance Using Just-in-Time (JIT) Code Generation for Matrix Multiplication (GEMM)

    The most commonly used and performance-critical Intel® Math Kernel Library (Intel® MKL) functions are the general matrix multiply (GEMM) functions.

Authored by Gennady F. (Blackbelt) Last updated on 03/21/2019 - 03:01
Article

Maximize TensorFlow* Performance on CPU: Considerations and Recommendations for Inference Workloads

This article will describe performance considerations for CPU inference using Intel® Optimization for TensorFlow*
Authored by Nathan Greeneltch (Intel) Last updated on 07/31/2019 - 12:11