Hcl Technologies Limited

Yogesh Gupta

Arvind Kumar Maurya

Dhanyamraju S U M Prasad

Harikrishna C Warrier

S U M Prasad Dhanyamraju

Vidhi Bajaj

Navin Saini

Parveen Kumar Jain

Mohammad Feroz Khan

Ravi Prasad

Praveen Kumar Jain

Himanshu Dubey

Karuna Sharma

Prathameshwar Pratap Singh

The disclosure relates to method and system recommending tuning of parameters to generate a data analytics model. The method includes identifying at a data pre-processing stage a pre-processing subset from an associated set of predefined pre-processing methods for a predefined objective. The method includes identifying at a feature selection stage a feature subset from an associated set of predefined feature selection methods for the predefined objective. The method includes identifying at a model training stage a training subset from an associated set of predefined model training methods for the predefined objective. The method further includes generating a plurality of data analytics tuples and selecting a data analytics tuple from the plurality of data analytics tuples. An output result of the data analytics tuple includes highest ranked results for the predefined objective.

Recommender system for tuning parameters to generate data analytics model and method thereof

The invention relates to method and system for providing visual explanations for image analytics decisions. The method includes extracting a set of local features from each of a plurality of image instances using a deep learning (DL) model; determining a feature list by aggregating the set of local features from each of the plurality of image instances; generating a two-dimensional (2D) pixel map based on the feature list; superimposing the 2D pixel map of aggregated features on each of the plurality of image instances; and providing a visual explanation for an image analytics decision on one or more of the plurality of image instances based on superimposition.

Method and system for providing visual explanations for image analytics decisions

This disclosure relates to method and system for managing items in warehouses through distributed ledger. The method includes sending a request from a first warehouse to each of a plurality of warehouses to add an item to an Enterprise Resource Planning (ERP) system associated with each of the plurality of warehouses and to a distributed ledger. For each of the plurality of warehouses, the method further includes checking whether the item exists in an ERP system associated with a warehouse based on the metadata of the item within the request from the first warehouse. The method further includes receiving a response to the request from each of the plurality of warehouses based on the checking. The method further includes managing the item in the ERP system associated with each of the plurality of warehouses and the distributed ledger based on the response received from each of the plurality of warehouses.

Method and system for managing items in warehouses through distributed ledger

A method and system for providing profile-based data and visualization access through a semantic domain layer is disclosed. In some embodiments, the method includes receiving a user request to access data. The method further includes determining a user profile from a plurality of user profiles associated with the user. The method further includes extracting a first access level from a first set of access levels associated with the user profile. The method further includes mapping the user profile with a domain object from a plurality of domain objects, based on a second access level from the first set of access levels associated with the domain object. The method further includes selectively rendering at least a portion of the data requested in the user request to the user, in response to mapping the user profile with the domain object.

Method and system for providing profile based data access through semantic domain layer

Disclosed is a system for translating data, extracted from disparate data sources, into a homogeneous dataset to provide meaningful information. The database schema definition module defines a database schema in order to extract meaningful information pertaining to a specific use-case. The data source determination module determines one or more disparate data sources pertinent to extract the meaningful information. The data extraction module extracts heterogeneous dataset from the one or more disparate data sources. The data extraction module further passes the heterogeneous dataset to a Data-Translate Markup Language (DTML) executer to translate the heterogeneous dataset into a homogeneous dataset. The data translation module translates the heterogeneous dataset into the homogeneous dataset by using at least one data adapter. In one aspect, the heterogeneous dataset may be translated to perform data analytics on the homogeneous dataset in order to provide the meaningful information pertaining to the specific use-case.

System for translating data, extracted from disparate datasources, based on a defined metadata and schema

The present subject matter discloses a system and method to enable a machine learning based analytics platform. The method may comprise generating a graphical user interface to enable one or more stakeholders to generate and manage a model for predictive analysis. The method may further comprise enabling a business user to define the business problem, and generate models to perform predictive analysis. The method may further comprise deploying the model, in a distributed environment, over a target platform. The method may further comprise monitoring the model to identify at least one error in the model and re-training the model for performing predictive analysis based on the at least one error, thereby enabling the machine learning based analytics platform.

Machine learning based analytics platform

The embodiments herein relate to operational data analysis (ODA) and, more particularly to automate operational data analysis and generate the analysis report for various products using a web-based multi-tenant product intelligence framework. The system allows the user to configure a data collection process, define schema structure, select a data storage for storing the collected data, select or create a data formatting algorithm, and generate a data report to perform the ODA process. Based on the ODA report, appropriate decisions can be taken by an organization.

System and method for automatically analyzing operational data using web-based multi-tenant product intelligence framework

The present disclosure relates to system(s) and method(s) for guiding a user in software development lifecycle using machine learning. The system is configured to receive real-time contextual information from a user device and user profile data from a profile database. Further, the system is configured to determine a current issue faced by the current user of the user device. In the next step, the system is configured to enforce a historical solution, from the set of historical solutions, associated with the current issue. If the historical solution is not applicable to address the current issue, the system is configured to extract one or more new solutions, from one or more secondary data sources. Finally, the system is configured to suggest the one or more new solutions to the current user, thereby guiding the current user to address the current issue.

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Noida, India

Yogesh Gupta