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Getting Started with Intel® Optimization for PyTorch* on Second Generation Intel® Xeon® Scalable Processors

Accelerate deep learning PyTorch* code on second generation Intel® Xeon® Scalable processor with Intel® Deep Learning Boost.
Автор: Nathan Greeneltch (Intel) Последнее обновление: 15.10.2019 - 16:50
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Large Matrix Operations with SciPy* and NumPy*: Tips and Best Practices

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Автор: Последнее обновление: 15.10.2019 - 21:16
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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.
Автор: Nguyen, Khang T (Intel) Последнее обновление: 09.12.2019 - 12:20
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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: 09.12.2019 - 12:20
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: 09.12.2019 - 12:20