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Five Key Features for a Machine Learning Platform

Anyscale · published 13 July 2020

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https://techcommunity.microsoft.com/t5/azure-ai/introducing-reinforcement-learning-on-azure-machine-learning/ba-p/1403028
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https://aws.amazon.com/blogs/aws/amazon-sagemaker-rl-managed-reinforcement-learning-with-amazon-sagemaker/
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https://ray.io/
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https://github.com/asappresearch/flambe
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The Future of Computing is Distributed Read at the source ↗
anyscale.com
https://medium.com/distributed-computing-with-ray/easy-distributed-scikit-learn-training-with-ray-54ff8b643b33
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https://thedataexchange.media/hyperscaling-natural-language-processing
thedataexchange.media
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https://docs.ray.io/en/releases-0.8.7/cluster/launcher.html
docs.ray.io
https://anyscale.com/blog/enterprise-applications-of-reinforcement-learning-recommenders-and-simulation-modeling/
anyscale.com
https://arxiv.org/abs/2004.13332
arxiv.org
https://docs.ray.io/en/latest/rllib.html
docs.ray.io
http://featurestore.org/
featurestore.org
https://eng.uber.com/michelangelo-machine-learning-platform/
eng.uber.com
https://en.wikipedia.org/wiki/Feature_(machine_learning
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https://www.wandb.com/
wandb.com
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comet.ml
https://en.wikipedia.org/wiki/MLOps
en.wikipedia.org
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https://www.datatron.com/
datatron.com
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https://www.tensorflow.org/tfx
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https://forms.gle/9TSdDYUgxYs8SA9e8
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https://events.linuxfoundation.org/ray-summit/?utm_source=ben&utm_medium=blog&utm_campaign=ray_summit
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