Streamz helps you build pipelines to manage continuous streams of data. It is simple to use in simple cases, but also supports complex pipelines that involve branching, joining, flow control, feedback, back pressure, and so on.
Optionally, Streamz can also work with both Pandas and cuDF dataframes, to provide sensible streaming operations on continuous tabular data.
To learn more about how to use Streamz see documentation at streamz.readthedocs.org.
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machine_learning_examples A collection of machine learning examples and tutorials.
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Turns your machine learning code into microservices with web API, interactive GUI, and more.
moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
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