A repository of material for the exercise classes of a Big Data Analytics master course. Hands-on sessions cover Spark and its machine learning library, Map/Reduce implementations of linear regression and alternating least squares, streaming analytics with Recursive Least Squares, and image classification with convolutional neural networks. Material is provided as Jupyter notebooks.
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Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, specialized for real-time large scale machine learning. It is a framework for building applications and includes packaged end-to-end applications for collaborative filtering, classification, regression and clustering. The repository was archived by the owner on May 3, 2022, and is read-only.
github.com
Analyzes structured data and helps produce queries, insights or visualizations.
github.com
XGBoost is a scalable, portable and distributed gradient boosting library. It supports multiple programming languages including Python, R, Java, Scala and C, and can run on single machines or distributed frameworks such as Hadoop, Spark, Dask, Flink and DataFlow.