Abstract: A method includes monitoring performance of a generated model while the generated model is being used for classification on live data, the monitoring including determining a first performance value of the generated model at a first point in time and determining a second performance value of the generated model at a second point in time; rendering, within a graphical user interface, a plot including a first axis and a second axis, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric; and rendering, within the graphical user interface and the plot, a first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes monitoring performance of a generated model while the generated model is being used for classification on live data, the monitoring including determining a first performance value of the generated model at a first point in time and determining a second performance value of the generated model at a second point in time; rendering, within a graphical user interface, a plot including a first axis and a second axis, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric; and rendering, within the graphical user interface and the plot, a first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes monitoring performance of a generated model while the generated model is being used for classification on live data, the monitoring including determining a first performance value of the generated model at a first point in time and determining a second performance value of the generated model at a second point in time; rendering, within a graphical user interface, a plot including a first axis and a second axis, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric; and rendering, within the graphical user interface and the plot, a first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes receiving, via a model building platform, historical user behavior including historical data analysis characteristics; generating, based on the historical data analysis characteristics, a blueprint for guiding user action to accomplish a task, the generating including constructing the blueprint using the historical data analysis characteristics; receiving, via graphical user interface, user input requesting generation of a model and a task description; determining, using the blueprint and based on the task description, data analysis characteristics; and rendering, within the graphical user interface, a prompt to select the determined data analysis characteristics. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes monitoring performance of a generated model while the generated model is being used for classification on live data, the monitoring including determining a first performance value of the generated model at a first point in time and determining a second performance value of the generated model at a second point in time; rendering, within a graphical user interface, a plot including a first axis and a second axis, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric; and rendering, within the graphical user interface and the plot, a first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes receiving, via a model building platform, historical user behavior including historical data analysis characteristics; generating, based on the historical data analysis characteristics, a blueprint for guiding user action to accomplish a task, the generating including constructing the blueprint using the historical data analysis characteristics; receiving, via graphical user interface, user input requesting generation of a model and a task description; determining, using the blueprint and based on the task description, data analysis characteristics; and rendering, within the graphical user interface, a prompt to select the determined data analysis characteristics. Related apparatus, systems, techniques and articles are also described.

Abstract: Performance of a first generated model can be monitored while the first generated model is deployed for use on live data. The monitoring can include determining a first performance value of the first generated model. Performance of a second generated model can be monitored while the second generated model is deployed for use on live data. The monitoring can include determining a second performance value of the second generated model. A plot including a first axis and a second axis can be rendered. The first axis can include a characterization of a first performance metric and the second axis can include a characterization of a second performance metric. A first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value can be rendered. Related apparatus, systems, techniques and articles are also described.

Abstract: A method can include receiving data characterizing a first property of an asset over a first time period. The method can also include receiving data characterizing user interaction with an interactive graphical object. The method can further include determining, by a predictive model, data characterizing the first property of the asset over a second time period. The determining can be based in part on the received data characterizing the user interaction. The method can also include rendering, in a graphical display space, one or more of a first plot of the received data characterizing the first property over the first time period and a second plot of the determined data characterizing the first property over the second time period.

Abstract: Performance of a first generated model can be monitored while the first generated model is deployed for use on live data. The monitoring can include determining a first performance value of the first generated model. Performance of a second generated model can be monitored while the second generated model is deployed for use on live data. The monitoring can include determining a second performance value of the second generated model. A plot including a first axis and a second axis can be rendered. The first axis can include a characterization of a first performance metric and the second axis can include a characterization of a second performance metric. A first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value can be rendered. Related apparatus, systems, techniques and articles are also described.

Abstract: A method can include receiving data identifying an industrial asset. The method can also include receiving data characterizing one or more sensors configured to detect a first property of the asset. The method can further include determining a first graphical representation of the asset based on the received data identifying the industrial asset, and a second graphical representation of a first sensor of the one or more sensors based on the received data characterizing one or more properties of one or more sensors. The method can further include rendering, in a graphical display space, the first graphical representation and the second graphical representation. One or more visual properties of the second graphical representation can be indicative of one or more properties of the first sensor and/or the detected first property of the asset.

Abstract: A method includes monitoring performance of a generated model while the generated model is being used for classification on live data, the monitoring including determining a first performance value of the generated model at a first point in time and determining a second performance value of the generated model at a second point in time; rendering, within a graphical user interface, a plot including a first axis and a second axis, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric; and rendering, within the graphical user interface and the plot, a first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes receiving, via a graphical user interface, data characterizing user input specifying a cost of error of a prediction, a model type requirement, and a computational resource allocation for model development; determining, based on the received data and using a model, a prediction of model performance; and rendering, within the graphical user interface, a plot including a first axis, a second axis, and a region characterizing the determined prediction of model performance, the first axis including a characterization of a first performance metric and the second axis including a characterization of a second performance metric. Related apparatus, systems, techniques and articles are also described.

Abstract: Performance of a first generated model can be monitored while the first generated model is deployed for use on live data. The monitoring can include determining a first performance value of the first generated model. Performance of a second generated model can be monitored while the second generated model is deployed for use on live data. The monitoring can include determining a second performance value of the second generated model. A plot including a first axis and a second axis can be rendered. The first axis can include a characterization of a first performance metric and the second axis can include a characterization of a second performance metric. A first graphical object at a first location characterizing the first performance value and a second graphical object at a second location characterizing the second performance value can be rendered. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes receiving, via a model building platform, historical user behavior including historical data analysis characteristics; generating, based on the historical data analysis characteristics, a blueprint for guiding user action to accomplish a task, the generating including constructing the blueprint using the historical data analysis characteristics; receiving, via graphical user interface, user input requesting generation of a model and a task description; determining, using the blueprint and based on the task description, data analysis characteristics; and rendering, within the graphical user interface, a prompt to select the determined data analysis characteristics. Related apparatus, systems, techniques and articles are also described.

Abstract: A method includes receiving data characterizing a target accuracy and a performance metric of a model; rendering, within a graphical user interface display space, a plot including a first axis and a second axis, the first axis including a characterization of false positive and the second axis including a characterization of false negative; and rendering, within the graphical user interface display space and within the plot, a graphical object at a location characterizing the performance metric and a visualization indicative of the target accuracy. Related apparatus, systems, techniques and articles are also described.

Abstract: A method can include receiving data characterizing a first property of an asset over a first time period. The method can also include receiving data characterizing user interaction with an interactive graphical object. The method can further include determining, by a predictive model, data characterizing the first property of the asset over a second time period. The determining can be based in part on the received data characterizing the user interaction. The method can also include rendering, in a graphical display space, one or more of a first plot of the received data characterizing the first property over the first time period and a second plot of the determined data characterizing the first property over the second time period.

Abstract: A method can include receiving data identifying an industrial asset. The method can also include receiving data characterizing one or more sensors configured to detect a first property of the asset. The method can further include determining a first graphical representation of the asset based on the received data identifying the industrial asset, and a second graphical representation of a first sensor of the one or more sensors based on the received data characterizing one or more properties of one or more sensors. The method can further include rendering, in a graphical display space, the first graphical representation and the second graphical representation. One or more visual properties of the second graphical representation can be indicative of one or more properties of the first sensor and/or the detected first property of the asset.

Abstract: Novel compounds of the general formula: and pharmaceutically acceptable acid addition salts thereof, wherein the compounds are useful in therapy to protect skeletal muscles against damage resulting from trauma or to protect skeletal muscles subsequent to muscle or systemic diseases such as intermittent claudication, to treat shock conditions, to preserve donor tissue and organs used in transplants, in the treatment of cardiovascular diseases including atrial and ventricular arrhythmias, Prinzmetal's (variant) angina, stable angina, and exercise induced angina, congestive heart disease, and myocardial infarction.

Abstract: Novel compounds of the general formula: and pharmaceutically acceptable acid addition salts thereof, wherein the compounds are useful in therapy to protect skeletal muscles against damage resulting from trauma or to protect skeletal muscles subsequent to muscle or systemic diseases such as intermittent claudication, to treat shock conditions, to preserve donor tissue and organs used in transplants, in the treatment of cardiovascular diseases including atrial and ventricular arrhythmias, Prinzmetal's (variant) angina, stable angina, and exercise induced angina, congestive heart disease, and myocardial infarction.

Abstract: Novel compounds of the general formula: 1