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APACHE MAHOUT
Distributed machine learning library built on Apache Spark
Apache-2.0
ABOUT
Training machine learning models on datasets too large for single-machine frameworks requires distributed computation. Apache Mahout provides scalable, tested implementations of ML algorithms that run on Spark clusters, enabling classification, clustering, and recommendation on petabyte-scale data without custom distributed programming.
INTEGRATION GUIDE
1. Build collaborative filtering recommendation systems that scale to millions of users and items
2. Train clustering and classification models on petabyte-scale datasets using Spark's distributed engine
3. Implement custom matrix factorization and linear algebra operations for large-scale ML pipelines
TAGS
machine-learningsparkdistributed-computingscalabig-datarecommendation