-
combust/mleap
MLeap: Deploy ML Pipelines to Production
Scala versions: 2.12 2.11 2.10 -
lucacanali/sparkmeasure
This is the development repository for sparkMeasure, a tool for performance troubleshooting of Apache Spark workloads. It simplifies the collection and analysis of Spark task and stage metrics data.
Scala versions: 2.13 2.12 2.11 -
scalapy/scalapy
Use the world of Python from the comfort of Scala!
Scala versions: 3.x 2.13 2.12 2.11Scala Native versions: 0.4 0.3 -
apache/sedona
A cluster computing framework for processing large-scale geospatial data
Scala versions: 2.13 2.12 2.11 -
locationtech-labs/geopyspark
GeoTrellis for PySpark
Scala versions: 2.11 -
isarn/isarn-sketches-spark
Routines and data structures for using isarn-sketches idiomatically in Apache Spark
Scala versions: 2.12 2.11 2.10 -
ozancicek/artan
Online latent state estimation with Spark
Scala versions: 2.12 2.11 -
salmon-brain/dead-salmon-brain
Apache Spark based framework for analysis A/B experiments
Scala versions: 2.12 2.11 -
timvw/adobe-analytics-datafeed-datasource
Apache Spark data source for Adobe Analytics Data Feed
Scala versions: 2.12 -
liquidsvm/liquidsvm
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
Scala versions: 2.11