Bosphorus AI Automated Machine Learning Platform supports all steps needed to prepare, build, deploy, monitor, and maintain powerful ML Applications at enterprise scale. Platform provides automated process of data collection, data storage, model configuration, model, deployment and model comparison in ML Projects. Platform also holds some common industry specific AI solutions which are fully integrated and ready to use.
Feature Store
Features are measurable variables which are observed and stored as data. In order to use models and make predictions we need features and thus they are main inputs of Machine Learning models. Features are stored and organized in “Feature Store”. The platform performs the feature engineering process using feature store capabilities.
ModelOps
Operationalization of ML models
ModelOps tools enable to manage the life cycle of machine learning models with visibility and control. Model interpretability, monitoring and continuous development are provided by ModelOps.
Complex Machine Learning Pipelines and End-to-end Auto ML
The platform provides domain-specific ML pipelines that can be optimized to find the best models efficiently. There are too many features that can be used as inputs and unlimited hyperparameters scenario. ML pipelines find the best models using feature engineering and hyperparameter tuning without human integration.
