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Informative Article | Engineering Science | India | Volume 8 Issue 7, July 2019 | Popularity: 4.7 / 10

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Survey on Real-Time Data Processing in Finance Using Machine Learning Techniques

Pushkar Mehendale

Abstract: Real-time data processing is transforming the financial industry by enabling applications that demand immediate insights and decisions. Machine learning (ML) techniques play a pivotal role in this transformation, with algorithms like Support Vector Machines (SVMs), Deep Neural Networks (DNNs), and Random Forests (RFs) widely used for tasks such as stock price prediction, credit risk assessment, fraud detection, and algorithmic trading. Frameworks like Apache Hadoop and Apache Spark facilitate efficient data handling and analysis, but challenges such as data volume and velocity, data variety, data quality, and latency need to be addressed for successful real-time data processing in finance.

Keywords: Machine Learning, Real-Time Data Processing, Finance, Apache Hadoop, Apache Spark

Edition: Volume 8 Issue 7, July 2019

Pages: 1910 - 1913

DOI: https://www.doi.org/10.21275/SR24810081140

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