Machine Learning Framework

A Machine Learning Framework is a software framework for machine learning systems.

• Context:
  • It can (typically) contain ML Libraries and ML Tools.
  • It can range from being a Neural Networking Framework, Decision Tree Ensemble Framework, ...
  • It can range from being a Distributed ML Framework, ...
  • It can range from being an Open Source ML Framework to being a Proprietary ML Framework.
  • It can be a ML Pipeline Framework, ...
  • It can be compatible with an ML Platform.
  • …
• Example(s):
  • scikit-learn;
  • Spark ML Module, Spark MLlib Module;
  • MLeap ML Pipeline Framework;
  • a Deep Learning Framework, such as:
    TensorFlow, Apache MXNet, PyTorch, Chainer;
  • Caffe, Caffe2;
  • Gluon;
  • Keras;
  • Microsoft Cognitive Toolkit.
  • …
• Counter-Example(s):
  • Machine Learning Tool.
  • Machine Learning Model Deployment System,
  • Machine Learning as a Service (MLaaS).
• See: Data Processing Framework, Machine Learning System, Deep Learning.

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