Abstract: Automatically detecting and anticipating that an additional machine learning experiment may be needed. A method includes after successfully running a first experiment workflow, automatically prompting a user that an additional experiment workflow may be needed based on specific criteria associated with the first experiment workflow. The method further includes receiving input from the user confirming the additional experiment workflow. As a result of receiving input from the user confirming the additional experiment workflow, the method further includes the system automatically reconfiguring the first experiment workflow, including automatically identifying all necessary modules for the additional experiment workflow and connecting them properly to perform the intended second experiment workflow. The method further includes displaying to the user the first experimental workflow transitioning from the first experiment workflow to the additional experiment workflow.

Abstract: Mismatches between schema elements of a data set and a job are identified automatically. Furthermore, the mismatches can be presented visually in conjunction with an interactive visual workspace configured to support diagrammatic authoring of data transformation pipelines. After a data set is connected to a job, one or more mismatches can be determined and presented in context with the workspace. In addition, schema elements can be reconfigured by way of interaction with a visual representation of schema elements to resolve mismatches.

Abstract: Automatically detecting and anticipating that an additional machine learning experiment may be needed. A method includes after successfully running a first experiment workflow, automatically prompting a user that an additional experiment workflow may be needed based on specific criteria associated with the first experiment workflow. The method further includes receiving input from the user confirming the additional experiment workflow. As a result of receiving input from the user confirming the additional experiment workflow, the method further includes the system automatically reconfiguring the first experiment workflow, including automatically identifying all necessary modules for the additional experiment workflow and connecting them properly to perform the intended second experiment workflow. The method further includes displaying to the user the first experimental workflow transitioning from the first experiment workflow to the additional experiment workflow.

Abstract: Automatically detecting and anticipating that an additional machine learning experiment may be needed. A method includes after successfully running a first experiment workflow, automatically prompting a user that an additional experiment workflow may be needed based on specific criteria associated with the first experiment workflow. The method further includes receiving input from the user confirming the additional experiment workflow. As a result of receiving input from the user confirming the additional experiment workflow, the method further includes the system automatically reconfiguring the first experiment workflow, including automatically identifying all necessary modules for the additional experiment workflow and connecting them properly to perform the intended second experiment workflow. The method further includes displaying to the user the first experimental workflow transitioning from the first experiment workflow to the additional experiment workflow.

Abstract: Automatically detecting and anticipating that an additional machine learning experiment may be needed. A method includes after successfully running a first experiment workflow, automatically prompting a user that an additional experiment workflow may be needed based on specific criteria associated with the first experiment workflow. The method further includes receiving input from the user confirming the additional experiment workflow. As a result of receiving input from the user confirming the additional experiment workflow, the method further includes the system automatically reconfiguring the first experiment workflow, including automatically identifying all necessary modules for the additional experiment workflow and connecting them properly to perform the intended second experiment workflow. The method further includes displaying to the user the first experimental workflow transitioning from the first experiment workflow to the additional experiment workflow.

Abstract: Mismatches between schema elements of a data set and a job are identified automatically. Furthermore, the mismatches can be presented visually in conjunction with an interactive visual workspace configured to support diagrammatic authoring of data transformation pipelines. After a data set is connected to a job, one or more mismatches can be determined and presented in context with the workspace. In addition, schema elements can be reconfigured by way of interaction with a visual representation of schema elements to resolve mismatches.

Abstract: A machine learning model deployment tool can receive a trained machine learning model and driven by a series of user interfaces and by received user input from the user interfaces, can automatically generate machine learning model software and deploy it to a hosting environment. The deployment of a machine learning model can be automated so that custom code does not have to be written by a human. Deployment can be to a single computing device, to a small scale service, to a small scale web service or to “the cloud”, e.g., as a high-scale, fault-tolerant web service utilizing hundreds of computers. Deployment can be guided by a series of user interfaces.

Abstract: User experience in a designer tool manages cogeneration of a database application and a database accessible through the application. A user places a visual representation of an application element designed to control a relational or hierarchical dataset. Code is automatically called to add the application element to the application, and automatically invoked to create database schema elements designed to implement the dataset in the database under application element control. Users verify that an application element has been automatically added, and confirm that database schema elements implementing the dataset(s) under control of the application element have been automatically created. A tutorial illustrates a workflow utilizing a designer tool to cogenerate a database application and a database without a data design step. A wizard utilizes the designer tool to cogenerate a database application and a database that collectively implement a calendar, a diagram, a tree, a wiki, and/or a list.

Abstract: User experience in a designer tool manages cogeneration of a database application and a database accessible through the application. A user places a visual representation of an application element designed to control a relational or hierarchical dataset. Code is automatically called to add the application element to the application, and automatically invoked to create database schema elements designed to implement the dataset in the database under application element control. Users verify that an application element has been automatically added, and confirm that database schema elements implementing the dataset(s) under control of the application element have been automatically created. A tutorial illustrates a workflow utilizing a designer tool to cogenerate a database application and a database without a data design step. A wizard utilizes the designer tool to cogenerate a database application and a database that collectively implement a calendar, a diagram, a tree, a wiki, and/or a list.

Abstract: The present invention extends to methods, systems, and computer program products for smart gestures for diagram state transitions. Embodiments of the invention expose a set of gestures and behaviors, which permit diagram transitions to be made with a reduced number of (and potentially a single) user gesture(s). For example, zoom levels can be toggled between a working zoom level and a zoom level sufficient to present an entire diagram and vice versa using a single user input gesture. Likewise, diagrams can be appropriately (and automatically) panned to make selected as well as newly created diagram elements visible in their entirety using a single user input gesture.