Apache SystemDS
A machine learning system for the end-to-end data science lifecycle, encompassing data integration, cleaning, feature engineering, efficient model training, and deployment.
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| + | Algorithm Customizability | Allows customization via R-like and Python-like languages |
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| + | Hybrid Execution Plans | Combines local, in-memory CPU and GPU operations with distributed operations on Apache Spark. |
| + | Multiple Execution Modes | Includes Spark MLContext, Spark Batch, Hadoop Batch, Standalone, and JMLC for varied operational needs. |
| + | Automatic Optimization | Optimizes based on data and cluster characteristics for efficiency and scalability. |
| + | Declarative Languages | Provides R-like syntax for various data science tasks |
| + | Compressed Linear Algebra | Enhances large scale machine learning |
| + | Principal Component Analysis | Provides scripts for statistical analysis |
| + | Compatibility | Compatibility with popular programming languages (Support for Java 11 and Python 3.5+) for broader use. |
| + | Integration | Works with Hadoop 3.3.x and Spark 3.5.x for big data processing. |
...7 more features/limitations. Contact us to get a complete list of features and system requirements.
System Requirements
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Ratings
4.005
| G2CROWD | 4.05 based on 1 reviews |
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Developer
Written in
Java, R, Python, Scala
Initial Release
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Repository
License
Categories
Alternatives
Notes
- Apache Spark is a prerequisite for installing Apache SystemDS. Hence, platforms for which Apache Spark is available are considered for Apache SystemDS.
- Apache SystemML is now Apache SystemDS.