Project Name
Intel Data Analytics Acceleration Library
Group Members
Jedd Chionglo Gabriel Dizon
Features
- Produce quicker and better predictions
- Analyze large datasets with available computer resources
- Optimize data ingestion and algorithmic compute simultaneously
- Supports offline, distributed, and streaming usage models
- Handles big data better than libraries such as Intel’s Math Kernel Library (MKL)
- Maximum Calculation Performance
- High-Speed Algorithms
Users of the Library
- Data Scientist
- Researchers
- Data Analysts
Data Analytics Pipeline
- The Intel® Data Analytics Acceleration Library provides optimized building blocks for the various stages of data analysis
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