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Machine Learning Development Environment
Data analytics requires a wide range of tools for a wide range of tasks: data collection, cleaning and labeling; model training and testing; presenting results, etc.
Our system is designed for both performance and ease of use. The software architecture is cleanly structured into layers, with the lowest one providing math and statistics functions, followed by a layer of machine learning and data handling tools. Templates for application domains are contained in the next layer, implemented in script language (Lua). These templates are adapted to customer requirements by field engineers when deploying applications at a customer premise.