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scikit-multiflow: Machine Learning for Data Streams in Python
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JACOB MONTIEL LOPEZ | POST DOCTORAL RESEARCHER AT TELECOM PARISTECH
As traditional "batch" learning is no match for today’s data deluge, a new field emerges — data stream mining. In stream learning, data is considered infinite and models are trained and updated continuously, thereby adapting to changes in the data. This talk provides an overview of data stream learning and introduces scikit-multiflow, an open-source Python framework to implement algorithms and perform experiments in the field of ML on evolving data streams.
As traditional "batch" learning is no match for today’s data deluge, a new field emerges — data stream mining. In stream learning, data is considered infinite and models are trained and updated continuously, thereby adapting to changes in the data. This talk provides an overview of data stream learning and introduces scikit-multiflow, an open-source Python framework to implement algorithms and perform experiments in the field of ML on evolving data streams.
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