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Windows® 10 May 2019 Update for Machine Learning Acceleration on Intel® Integrated Graphics

Intel's earlier post in May 2018 introduced the Windows ML API and the DirectML API implementation on Intel® hardware via the DirectX 12 DirectCompute

Introduction to the Intel® Distribution of OpenVINO™ Toolkit and Windows Machine Learning*

Última actualización: 13 de mayo de 2019Duración de video: 1 min

In this webinar you will learn how real-time inference on the PC for visual workloads such as object detection, recognition, and tracking are now easily developed with Intel® Distribution of OpenVINO™ Toolkit and Windows Machine Learning* API.

Introduction to Natural Language Processing (NLP) Architect

Última actualización: 13 de mayo de 2019Duración de video: 52 min

This webinar focuses on introducing the audience to Natural Language Processing (NLP) Architect, a Python* library from the Intel® AI Lab for exploring the state-of-the-art deep learning topologies.

Intel® CPU Outperforms NVIDIA* GPU on ResNet-50 Deep Learning Inference

Intel Xeon processor outperforms NVidia's best GPUs on ResNet-50.

Detecting Acute Lymphoblastic Leukemia Using Caffe*, OpenVINO™ and Intel® Neural Compute Stick 2: Part 1

First part of a series that will take you through my experience building a custom classifier with Caffe* that should be able to detect AML/ALL.

Object Detection: A Comparison of Performance of Deep Learning Models on Edge Using Intel® Movidius™ Neural Compute Stick and Raspberry PI* 3

Última actualización: 18 de abril de 2019

Vehicle Detection involves finding whether there is vehicle present or not secondly which type of vehicle is present and how many vehicles are...

Towards Privacy-Preserving Machine Learning

Última actualización: 18 de abril de 2019

When Artificial Intelligence involves some type of sensitive data, the problem is how to maintain the data privacy and security. This problem...

Implementing Attention Models in PyTorch*

Última actualización: 18 de abril de 2019

Recurrent Neural Networks have been the recent state-of-the-art methods for various problems whose available data is sequential in nature. Adding...

Distributed Training of Deep Learning Models with PyTorch*

Última actualización: 18 de abril de 2019

The motive of this article is to demonstrate the idea of distributed computing in the context of training large scale deep learning (DL) models....

Ben: The Self-Driving Bot

Ben is an autonomous, self-driving robot built on Intel® architecture.

Introduction to Reinforcement Learning Coach

Última actualización: 16 de abril de 2019Duración de video: 50 min

Introducing Reinforcement Learning (RL) Coach.

Transitioning from Intel® Movidius™ Neural Compute SDK to Intel® Distribution of OpenVINO™ toolkit

This article provides guidance for transitioning from the NCSDK to the Intel® Distribution of OpenVINO™ toolkit.

Code Sample: Intel® AVX512-Deep Learning Boost: Intrinsic Functions

How developers can use to take advantage of the new Intel® AVX512-Deep Learning Boost (Intel® AVX512-DL Boost) instructions.

Intel and Facebook* collaborate to boost PyTorch* CPU performance

Intel's software optimization and 2nd generation Intel® Xeon® Scalable Processors with Intel® DL Boost® accelerate PyTorch's CPU performance

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Second Generation Intel® Xeon® Processor Scalable Family Technical Overview

New features and enhancements available in the second generation Intel® Xeon® processor Scalable family and how developers can take advantage of them

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.

Detecting Acute Lymphoblastic Leukemia Using Caffe*, OpenVINO™ and Intel® Neural Compute Stick 2: Part 2

In this article I will cover the steps required to create the dataset required to train the model using the network we defined in the last tutorial.

Reducing False Negatives in the Invasive Ductal Carcinoma Classifier

This project tries to trick the model by using very similar, but opposite class, images from a small set of testing data that we believe humans may...

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

Publicado el 6 de septiembre de 2018, actualizado el 15 de marzo de 2019Por Gennady F.

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

Getting to Know the Intel® Neural Compute Stick 2

Última actualización: 13 de marzo de 2019Duración de video: 48 min

In this webinar you’ll get an overview of the Intel® Neural Compute Stick 2 (Intel® NCS 2), what it is good for, and see how easy it is to get started.

Acute Myeloid/Lymphoblastic Leukemia Data Augmentation

The AML/ALL Classifier Data Augmentation program applies filters to datasets and increases the amount of training and test data available to use.

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How AI is Helping Us Better Understand the Environment

Publicado el 5 de marzo de 2019

Success Story: Researchers use AI techniques to help understand ecosystems better to analyze the complex interactions and patterns in our environment.

Deep Learning with Analytic Zoo Optimizes Mastercard* Recommender AI Service

Introduces a joint initiative between Mastercard* and Intel in building users-items propensity models for a universal recommender AI service.

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Computer Vision Annotation Tool: A Universal Approach to Data Annotation

At Intel, one of the projects we’re undertaking research on is developing computer vision algorithms based on deep neural networks (DNNs) and how...

Talroo* Uses Analytics Zoo and AWS* to Leverage Deep Learning for Job Recommendations

This project demonstrates how to leverage the natural language context analysis and recommender models of Analytics Zoo on Amazon Web Services (AWS*)

Detecting Invasive Ductal Carcinoma with Convolutional Neural Networks

This article, Machine Learning and Mammography, shows how existing deep learning technologies can be utilized to train artificial intelligence (AI)...

Flower

Identify Plant Anatomy Using the Intel® Distribution of OpenVINO™ Toolkit

Use Case: Build a model to identify plant anatomy with the Intel® Distribution of OpenVINO™ Toolkit

Optimization Practice of Deep Learning Inference Deployment on Intel® Processors

Publicado el 19 de febrero de 2019

Optimize performance of inference service on CPUs and save computing resources using the iQIYI deep learning cloud platform

Inception V3 Deep Convolutional Architecture For Classifying Acute Myeloid/Lymphoblastic Leukemia

Inception V3, transfer learning, and how we use these tools in the Acute Myeloid/Lymphoblastic Leukemia AI Research Project.

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Implement Hand Gesture Recognition with XRDrive Sim

Showcases the implementation of object detection on a PC video stream using the Intel® Distribution of OpenVINO™ toolkit on Intel® processors

Hands-On AI Part 17: Emotion Recognition from Images Baseline Model

Publicado el 25 de octubre de 2017, actualizado el 29 de enero de 2019

In this article, we will be building a baseline Convolutional Neural Network (CNN) model that is able to perform emotion recognition from images....

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*

Vehicle Advanced Monitoring System (VAMS)

This vehicle advanced monitoring system solution is intended for vehicular systems supporting the CAN protocol.

AI Practitioners Guide for Beginners

TensorFlow* Framework Deployment and Example Test Runs on Intel® Xeon® Platform-Based Infrastructure

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Cash Recognition for the Visually Impaired: Part 3

Cash Recognition for the Visually Impaired: A project to make monetary transactions easier for visually impaired Nepalese with machine learning and AI

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