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

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

Profiling TensorFlow* workloads with Intel® VTune™ Amplifier

This tutorial will show how to combine the data provided by TensorFlow*.timeline with options available in one of the most powerful performance profilers for Intel® Architecture – Intel® VTune™ Amplifier.
Автор: Alexandr Kurylev (Intel) Последнее обновление: 21.03.2019 - 09:54

Explore Unity Technologies ML-Agents* Exclusively on Intel® Architecture

This article describes how to install and run Unity Technologies ML-Agents* in CPU-only environments.
Автор: Bryan B. (Intel) Последнее обновление: 05.07.2019 - 18:54

Get Started With Unity* Machine Learning Using Intel® Distribution for Python* (Part 1)

This article will show game developers how to use reinforcement learning to create better artificial intelligence (AI) behavior. Using Intel® Distribution for Python—an improved version of the popular object-oriented, high-level programming language—readers will glean how to train pre-existing machine-language (ML) agents to learn and adapt. In this scenario, we will use Intel® Optimization for...
Автор: Manisha B. Последнее обновление: 31.12.2018 - 14:00

使用 Python* 的英特尔® 分发版实现 Unity* 机器学习入门(第 1 部分)

本文将向游戏开发人员介绍如何使用强化学习创建更好的人工智能 (AI) 行为。使用 Python* 的英特尔® 分发版 — 常用面向对象的高级编程语言的进阶版 — 读者可收集关于如何训练预先存在的机器语言 (ML) 代理学习和适应的信息。在此场景下,我们将使用英特尔® Optimization for TensorFlow* 在本地化环境中运行 Unity * ML-Agents。
Автор: Manisha B. Последнее обновление: 27.07.2018 - 03:50

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: 15.08.2019 - 12:50