Build High-Performance Data Science and Machine Learning Applications

Intel® oneAPI Data Analytics Library (oneDAL) accelerates big data analysis at all stages of the machine learning pipeline. This open source, cross-platform library provides implementations of classical machine learning algorithms that are optimized for Intel CPUs and GPUs. Using this library, you can:

• Make better predictions faster.
• Optimize data ingestion and algorithmic compute simultaneously.
• Develop offline, streaming, and distributed use models.
• Split analytics workloads between edge devices and cloud to optimize overall application throughput. oneDAL optimizes algorithms from popular machine learning Python* libraries such as XGBoost and Intel® Extension for Scikit-learn*, which are part of the end-to-end suite of Intel® AI and machine learning development tools and resources.

Features

• High-Speed Algorithms: Includes optimized functions for analysis, math, training, and prediction.
• Cross-Platform: Compatible with various platforms for flexible deployment.
• Machine Learning Optimization: Enhances performance of popular machine learning libraries like XGBoost and Scikit-learn.
• Big Data Analysis: Accelerates big data analysis across the entire machine learning pipeline.
• Edge and Cloud Integration: Supports splitting analytics workloads between edge devices and cloud.