Description
Intel® oneAPI AI Analytics Toolkit
Intel® oneAPI AI Analytics Toolkit - Achieve End-to-End Performance for Data Science and AI Workloads
Accelerate Data Science & AI Pipelines
The Intel® oneAPI AI Analytics Toolkit gives data scientists, AI developers, and researchers familiar Python* tools and frameworks to accelerate end-to-end data science and machine learning pipelines on Intel® architectures. The components are built using oneAPI libraries for low-level compute optimizations. This toolkit maximizes performance from preprocessing through machine and deep learning phases and provides interoperability for efficient model development and deployment across single and multinodes.
Using this toolkit, you can:
- Deliver high-performance deep learning (DL) training and inference on Intel® XPUs with Intel-optimized DL frameworks: TensorFlow* and PyTorch*, pretrained models, and Intel Low Precision Optimization Tool.
- Achieve drop-in acceleration for data preprocessing and machine learning workflows with compute-intensive Python packages: Modin*, Scikit-Learn*, and XGBoost* optimized for Intel.
- Seamlessly scale up and scale out to leverage AI compute continuum across single and multi nodes
- Gain direct access to Intel’s latest machine and deep learning optimizations in a single integrated package tested for interoperability.
The Intel® oneAPI AI Analytics Toolkit includes the following components:
- Intel® Optimization for TensorFlow
- Intel® Optimization for PyTorch
- Intel® Extension for Scikit-Learn*
- Intel Optimized XGBoost
- Intel® Distribution of Modin
- Intel® Low Precision Optimization Tool
- Model Zoo for Intel® Architecture
- Intel® Distribution for Python
Documentation and Resources
For even more examples and information on AI Kit optimizations consider visiting the following resources:
Intel® oneAPI AI Analytics Toolkit Website
Intel® oneAPI AI Analytics Toolkit Code Samples
Intel® oneAPI AI Analytics Toolkit Release Notes
Intel® oneAPI AI Analytics Toolkit Support Forum
