We are pleased to announce the release of Intel® Data Analytics Acceleration Library 2016 Beta!
Intel® Data Analytics Acceleration Library is a C++ and Java API library of optimized analytics building blocks for all data analysis stages, from data acquisition to data mining and machine learning. It is a library essential for engineering high performance data application solutions.
To join the free Beta program and get instructions on downloading the software, please send a note to intel.daal@intel.com.
This is the initial Beta release and it has introduced many features including:
- C++ and Java programming languages API.
- Data mining and analysis algorithms for
- Computing correlation distance and Cosine distance
- PCA (Correlation, SVD)
- Matrix decomposition (SVD, QR, Cholesky)
- Computing statistical moments
- Computing variance-covariance matrices
- Univariate and multivariate outlier detection
- Association rule mining
- Algorithms for supervised and unsupervised machine learning:
- Linear regressions
- Naïve Bayes classifier
- AdaBoost, LogitBoost, and BrownBoost classifiers
- SVM
- K-Means clustering
- Expectation Maximization (EM) for Gaussian Mixture Models (GMM)
- Support for local and distributed data sources:
- In-file and in-memory CSV
- MySQL
- HDFS
- Support for Resilient Distributed Dataset (RDD) objects for Apache Spark*.
- Data compression and decompression:
- ZLIB
- LZO
- RLE
- BZIP2
- Data serialization and deserialization.
To join the free Beta program and get instructions on downloading the software, please send a note to intel.daal@intel.com. This program will end in late June 2015. During the program, we will contact you to gain feedback. Please join other users in discussions about Intel Data Analytics Acceleration Library on the User Forum.
Thank you for your interest in Intel Data Analytics Acceleration Library. Let us know how we can help you!