The machine learning project on top of Rheem
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ML4all: scalable ML system for everyone

ML4all is a system that frees users from the burden of machine learning algorithm selection and low-level implementation details. It uses a new abstraction that is capable of solving most ML tasks and provides a cost-based optimizer on top of the proposed abstraction for choosing the best gradient descent algorithm in a given setting. Our results show that ML4all is more than two orders of magnitude faster than state-of-the-art systems and can process large datasets that were not possible before.

More details can be found in our SIGMOD publication:

Currently running on:

  • Rheem 0.3.0
  • Spark 1.6.x

Some examples can be found in org.qcri.ml4all.examples:

  • kmeans: RunKmeans
  • sgd: RunSGD