DMLC
Distributed Multiple Learning Cores (DMLC) is a framework for distributed machine learning that allows for parallel training of models across multiple computing nodes. It is commonly used in the maritime industry for tasks such as vessel classification, anomaly detection, and predictive maintenance. DMLC enables the use of large datasets and complex models that would be otherwise infeasible to train on a single machine. The framework is designed to be scalable, fault-tolerant, and efficient, and can be used with a variety of machine learning libraries such as TensorFlow, MXNet, and XGBoost.
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