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Webinar: Deep Learning 101

Deep neural networks are capable of amazing levels of representation power resulting in state-of-the-art accuracy in areas such as computer vision, speech recognition, natural language processing,

Authored by Andres Rodriguez (Intel) Last updated on 10/24/2018 - 15:36
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
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Optimize Linear Regression Model with Intel® DAAL

This article describes a common type of regression analysis called linear regression and how the Intel® Data Analytics Acceleration Library helps optimize this algorithm on Intel® Xeon® processors.
Authored by Nguyen, Khang T (Intel) Last updated on 02/25/2019 - 11:43
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How to Install the neon™ Framework on Ubuntu*

This article presents a simple step-by-step way to install the neon framework in Ubuntu* 14.04 using the Anaconda* Python* distribution. It also guides users through what to do if errors are encountered during the installation process.
Authored by Nguyen, Khang T (Intel) Last updated on 06/10/2018 - 21:00
Article

BigDL: Bring Deep Learning to the Fingertips of Big Data Users and Data Scientists

Big data and analytics play a central role in today’s smart and connected world, and are continuously driving the convergence of big data, analytics, and machine learning/deep learning. We open sourced BigDL, a distributed deep learning library for Apache Spark*, for the very purpose of uniting the deep learning community and the big data community
Authored by Jason Dai (Intel) Last updated on 03/11/2019 - 13:17
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Build and Install TensorFlow* Serving on Intel® Architecture

The information provided in this paper describes how to build and install TensorFlow* Serving, a high-performance serving system for machine learning models designed for production environments.
Authored by Bryan B. (Intel) Last updated on 06/29/2018 - 14:29
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Train a TensorFlow* Model on Intel® Architecture

In this paper, you will learn how to train and save a TensorFlow* model, build a TensorFlow model server, and test the server using a client application. 
Authored by Bryan B. (Intel) Last updated on 06/29/2018 - 14:40
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An Example of a Convolutional Neural Network for Image Super-Resolution

Convolutional Neural Networks (CNN) are becoming mainstream in computer vision. In particular, CNNs are widely used for high-level vision tasks, like image classification. This article describes an example of a CNN for image super-resolution (SR), which is a low-level vision task, and its implementation using the Intel® Distribution for Caffe* framework and Intel® Distribution for Python*.
Authored by Alberto V. (Intel) Last updated on 01/24/2018 - 15:35
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An Example of a Convolutional Neural Network for Image Super-Resolution—Tutorial

This tutorial describes one way to implement a CNN (convolutional neural network) for single image super-resolution optimized on Intel® architecture from the

Authored by Alberto V. (Intel) Last updated on 02/18/2019 - 11:57