microsoft-machine-learning
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Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
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Jul 25, 2019 - Jupyter Notebook
An unofficial Microsoft Machine Learning Server Docker image.
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Oct 6, 2017
Re-implementation and extension of the work described in "Learning to Represent Programs with Graphs"
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May 14, 2019 - Python
A web mapping app to test, tweak and train the land cover classification from a deep neural network model built by@microsoft
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May 24, 2018 - JavaScript
Machine learning projects implemented by ML.NET using F#
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Jun 6, 2018 - F#
A collection of Microsoft ML experiment Jupyter notebooks.
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Oct 20, 2017 - Jupyter Notebook
Repository for Microsoft Machine Learning
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Nov 11, 2022 - Jupyter Notebook
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