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Protect Big Data now with better tools On April 05, Monday, 2021

Data scientists need increasingly powerful methods of machine learning to extract useful information from big data. Dr. Aria Nosratinia has received two grants from the National Science Foundation totaling $749,492. His research aims to uncover relationships hiding in big data via machine learning. The University of Texas at Dallas professor also wants to develop methods to keep data communications safe. "The contribution of my lab is to expand the universe of tools and techniques," he says.

Read more at techxplore.com

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Financial Institutions dealing with Unstructured Data On March 15, Monday, 2021

Less than 1% of all unstructured data is analyzed or used in any way. Financial institutions are turning to AI to help them power decision-making. Big data analytics solutions which leverage machine learning (ML) can parse through data to identify important information. These tools can uncover new market insights, allowing teams at investment management firms to get a deeper understanding of businesses. HSBC recently launched a "world-first" AI-powered investment index, which cleanse unstructured data from sources such as tweets, satellite imagery.

Read more at insidebigdata.com

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Algorithm that reduces complexity of Big Data On March 11, Thursday, 2021

A Texas A&M doctoral student has developed a machine-learning algorithm applicable to large datasets. The algorithm can extract and directly order features from most salient to least. The work to find or develop these types of algorithms has been going on for the past century. A paper describing the research was published in the 2020 International Conference on Machine Learning. The paper was written by Reza Oftadeh and Dr. Dylan Shell of the Department of Computer Science and Engineering.

Read more at techxplore.com

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