The subject technology receives information associated with a machine learning model. The subject technology determines a set of metrics based at least in part on the information associated with the machine learning model, where the set of metrics corresponds to respective indicators of performance of the machine learning model based on input data from a data set, the set of metrics further including a number of errors produced by the machine learning model when applied to the input data from the data set. Further, the subject technology displays a user interface based at least in part on the set of metrics, where the user interface includes a set of graphical elements, and the set of graphical elements further includes representations of the set of metrics, and representations of the input data from the data set utilized by the machine learning model.

The subject technology receives information associated with a machine learning model. The subject technology determines a set of metrics based at least in part on the information associated with the machine learning model, where the set of metrics corresponds to respective indicators of performance of the machine learning model based on input data from a data set, the set of metrics further including a number of errors produced by the machine learning model when applied to the input data from the data set. Further, the subject technology displays a user interface based at least in part on the set of metrics, where the user interface includes a set of graphical elements, and the set of graphical elements further includes representations of the set of metrics, and representations of the input data from the data set utilized by the machine learning model.

An information processing apparatus according to one embodiment includes one or more hardware processors coupled to a memory. The one or more hardware processors acquires pieces of target data of different types. The one or more hardware processors generates element information for each element included in the pieces of the target data. The element information indicates the corresponding element. The one or more hardware processors links, with each other, related pieces of the element information and stores the linked pieces of the element information in a storage device.

An information processing apparatus according to one embodiment includes one or more hardware processors coupled to a memory. The one or more hardware processors acquires pieces of target data of different types. The one or more hardware processors generates element information for each element included in the pieces of the target data. The element information indicates the corresponding element. The one or more hardware processors links, with each other, related pieces of the element information and stores the linked pieces of the element information in a storage device.

This disclosure provides a system and method for providing intelligently-selected collections of user-centric content in a web browser. When implemented as a method, the method includes maintaining a user-centric graph with a plurality of user-centric facts derived from user interaction with different computer services. The method further includes recognizing different contexts of interest to the user. For each context, a collection of user-centric facts pertaining to the context are recognized in the user-centric graph, such recognition being based on a relationship between user-centric facts in the user-centric graph. The method further includes, for each context, displaying intelligently-selected content based on the collection of user-centric facts.

Systems and methods are disclosed for processing events having raw machine data associated with a timestamp using one or more pivot identifiers and one or more step identifiers to generate one or more journey instances. Based on the one or more pivot identifier field, the system can relate events that have a common field value for the pivot identifier field. Based on the one or more step identifiers, the system can group the related events into a subset of events. Using the subset of events, the system can build a journey instance.

An aircraft noise monitoring system uses a set of geographically distributed noise sensors to receive data corresponding to events captured by the noise sensors. Each event corresponds to noise that exceeds a threshold level. For each event, the system will receive a classification of the event as an aircraft noise event or a non-aircraft noise event. It will then use the data corresponding to the events and the received classifications to train a convolutional neural network (CNN) in a classification process. After training, when the system receives a new noise event, it will use the CNN to classify the new noise event as an aircraft noise event or a non-aircraft noise event, and it will generate an output indicating whether the new noise event is an aircraft noise event or a non-aircraft noise event.

An aircraft noise monitoring system uses a set of geographically distributed noise sensors to receive data corresponding to events captured by the noise sensors. Each event corresponds to noise that exceeds a threshold level. For each event, the system will receive a classification of the event as an aircraft noise event or a non-aircraft noise event. It will then use the data corresponding to the events and the received classifications to train a convolutional neural network (CNN) in a classification process. After training, when the system receives a new noise event, it will use the CNN to classify the new noise event as an aircraft noise event or a non-aircraft noise event, and it will generate an output indicating whether the new noise event is an aircraft noise event or a non-aircraft noise event.

An object is recognized from image data as a target object and linked to a user based on an interaction by the user, information about the target object is obtained and a purchase of the target object is initiated.

The disclosure is related to a method for providing an interactive menu data for contents search. At least one query word may be generated based on user inputs at user equipment. A server may generate an interactive menu data based on the received at least one query word. The server may provide the generated interactive menu data to the user equipment.