Apache PredictionIO
Apache PredictionIO: Open Source Machine Learning Server
Open source machine learning server for developers to create predictive services, supporting recommendations, content discovery, machine learning workflows, anomaly detection, and more.
What is Apache PredictionIO?
Apache PredictionIO is an open source machine learning server built on Apache Spark, HBase, and Spray that helps developers create predictive services for various use cases like personalized recommendations, predictive analytics, machine learning workflows, and more.
It supports building, evaluating and deploying engines for machine learning tasks like classification, regression, clustering, collaborative filtering, and anomaly detection. The event server allows collecting event data from apps and web services to power the engines.
PredictionIO comes bundled with template engines like Recommendation engine for personalized recommendations, Classification engine for text classification, Affinity Analysis engine for item similarities/associations, and Anomaly Detection engine. It simplifies machine learning for developers to get started quickly without needing to train models from scratch.
Key capabilities include scalability to large data volumes with Spark integration, easy-to-use REST APIs, reusable template engines, instant recommendations via Online Personalization, and PMML model support. It can be deployed on-premise or on the cloud.
Apache PredictionIO Features
Features
- Open source machine learning server
- Supports building predictive engines for recommendations, content discovery, machine learning workflows, anomaly detection, etc
- Has SDKs for Java, Python, Scala, PHP, Ruby, etc to build and deploy engines
- Built on technologies like Apache Spark, HBase, Spray, Elasticsearch, etc
- Has data source connectors for common data stores
- Template gallery with pre-built engines like recommendation, classification, regression, etc
- Web UI and REST API for engine management and deployment
Pricing
- Open Source
Pros
Cons
Official Links
Reviews & Ratings
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