Library

Content Type

OK

Cancel

Topic

OK

Cancel

Technologies

OK

Cancel

Tools and SDKs

OK

Cancel

IDE/Framework/Engine

OK

Cancel

Hardware and Developer Kits

OK

Cancel

Middleware

OK

Cancel

Programming Language

OK

Cancel

Operating System

OK

Cancel

Applied Filters

This sample illustrates how to set up and train an XGBoost* model on datasets for prediction. It uses Intel optimized XGBoost from AI Kit.

This sample shows how to use Intel Modin from AI Kit.

This sample shows how to use Intel Low Precision Optimization Tool from AI Kit.

This sample demonstrates the performance advantage of using Intel TF from AI Kit vs Stock TF

This sample code shows how to scale DL training to multi-nodes using Intel PyTorch and oneCCL bindings, part of AI Kit

This sample code shows how to get started with scaling out the training of a neural network to multiple compute nodes in a cluster using Intel TensorFlow and Horovod in AI Kit

This sample will demonstrate how to take advantage of Auto mixed-precision which is part of Intel optimization for PyTorch

This is a ResNet50 v1.5 FP32 training package optimized with TensorFlow* for Kubernetes*.

Intel® oneAPI Toolkits

Intel® oneAPI products deliver the freedom to develop with a unified toolset and to deploy applications and solutions across CPU, GPU, and FPGA architectures.

Learn more about key components, add-ons, tools, models, demos, and more for the Intel Distribution of OpenVINO toolkit.

Get up-to-speed fast using resources and training materials for this computer vision toolkit.

Emulate human vision in applications across Intel® hardware, as well as extend workloads and maximize performance.