International Business Machines Corporation

Sundari Voruganti

Ramani Ranjan Routray

Denilson Nastacio

Sriram Srinivasan

Abhinandan Kelgere Ramesh

Michele Chilanti

Lalit Somavarapha

Vikram Sri Nitesh Tantravahi

Hanging Chen

Kevin M Lefebvre

Ankit Jha

An approach for assessing a user experience with a product deployment. The approach embeds markers in documentation associated with a product. The approach embeds the markers in the product, correlated with the marker positions in the documentation. The approach calculates metrics, associated with timings between markers, based on deployment of the product by a user. The approach generates a report of an experience of the user in deploying the product.

Automated product workflow usability assessment

In an approach for visualizing metrics towards optimizing application performance, a processor identifies an application, running in a user interface, on a cloud platform. A processor calculates information metrics of the application. A processor presents the information metrics on the user interface with the application.

Inspection mechanism framework for visualizing application metrics

A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to configure the processor to implement a cognitive service for cognitive model tuning with rich deep learning knowledge. The mechanism performs a first model training operation and records training data set and hyperparameter information for the model in a database. The mechanism performs a model testing operation using a testing data set and records metric values that result from the model testing in the database. For a next model training operation for a given model, the mechanism performs an anomalies check for the given model. The mechanism performs a difference comparison on the training data set, hyperparameter information, and the metric values. The mechanism generates a recommendation of a training data set and hyperparameters for the next model training operation. The mechanism performs the next model training operation.

Cognitive model tuning with rich deep learning knowledge

Growing community of inventors

San Jose, CA, United States of America

Sundari Voruganti