endymecy/spark-ml-source-analysis

Provides in-depth algorithmic analysis and distributed implementation details for 30+ Spark ML algorithms across classification, clustering, dimensionality reduction, and feature engineering, covering both mathematical foundations and Scala source code walkthroughs. Targets Spark 1.6.1 and 2.x versions with comprehensive documentation of optimization techniques (gradient descent, L-BFGS, NNLS) and tree-based ensemble methods. Structured as an educational reference covering statistical foundations, collaborative filtering via ALS, and feature transformation pipelines through detailed code commentary and formula derivations.

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