Learn how to train a ML model in a distributed fashion without reformatting our code on Databricks with Maggy, open source tool available on Hopsworks.
read moreHopsworks supports machine learning experiments to track and distribute ML for free and with a built-in TensorBoard.
read moreAnomaly detection and Deep learning for identifying money laundering . Less false positives and higher accuracy than traditional rule-based approaches.
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Maggy is a framework for distribution transparent machine learning experiments on Apache Spark.
Maggy lets you reuse training codes whether you are training small models on a laptop or scaling out hyperparameter tuning or distributed deep learning on a cluster.
Maggy can replace the current waterfall development process for distributed ML applications, where code is rewritten at every stage in order to account for the different distribution context.
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