MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118156 A) filed by Ms. Mohammad Nourien; Mr. Ankam Dhilli Babu; Mr. Bhupesh Pandey; Mr. Bodicherla Siva Sankar; Dr. Nellore Manoj Kumar; and Dr. S. Rama on October 01, 2026, for A Machine Learning-Based Automated Feature Learning And Prediction System For Large-Scale Data Analytics.
Inventors include Ms. Mohammad Nourien; Mr. Ankam Dhilli Babu; Mr. Bhupesh Pandey; Mr. Bodicherla Siva Sankar; Dr. Nellore Manoj Kumar; and Dr. S. Rama.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: A machine learning-based automated feature learning and prediction system for large-scale data analytics is disclosed. A data ingestion component receives raw large- scale, high-dimensional data for an analytics task. A feature learning component, comprising a machine learning model such as a representation-learning or deep- learning model, learns automatically from the raw data the features and representations predictive of an outcome, discovering them from the data, including features a human would not conceive, in place of the manual feature engineering that is the laborious, slow, expertise-dependent, human-limited, and poorly-scaling bottleneck of conventional analytics. A prediction component, comprising a predictive model trained on the automatically learned features, predicts the outcome. In embodiments the feature learning and prediction are integrated in an end-to-end deep learning model that learns features and prediction jointly from the raw data, optimizing the features for the prediction. The system operates on large-scale, high-dimensional data at scale by distributed and parallel computation that manual engineering could not handle, automating the analytics end-to-end from raw data to prediction, faster, cheaper, and more effectively than manual-feature-engineering analytics and at greater scale.
Disclaimer: Curated by HT Syndication.
