Aspen Data Science Studio is a fully managed ML studio allowing data scientists to develop, train & test, productize and run models and other heuristics. Leveraging fully hosted and managed Jupyter notebooks, it provides a workbench for feature engineering, collaboration, versioning, model productization and much more. Data Science Studio also promotes a ‘bring your own model’ approach by allowing data science teams to leverage their own preferred libraries.
Our Data Science studio is a collaborative tool that helps you develop, productize and share machine learning models on IoT data.
Aspen Data Science Studio allows you to train, test, deploy and run models more efficiently.
Aspen Data Science Studio provides a hosted and fully managed Python notebook development environment in which you can leverage your preferred ML libraries. Custom dependency sets can also be added to streamline the development of proprietary intellectual properties.
Train, test, and version models on live streaming data, and/or archived data. Aspen Data Science Studio has a flexible sandbox and production environment which allows users to easily experiment and validate models.
Aspen Data Science Studio packages models into a function-as-a-service container. Productize your models on-demand to internal or external applications through a one-click deployment process or store them in a blob store for easy retrieval and scheduling.
Schedule the training and prediction of your ML models and save prediction indexes for quick retrieval. Export your insights and predictions to third-party systems and solutions using a secure JSON REST API call.
Easily examine and benchmark KPIs for model performance. Develop custom KPIs or leverage native analytics standards to ensure your ML models and workflows continue to perform over time.