Aug 20, 2020 · A machine learning algorithm (MLA) is an approach or tool to help in big data analytics (BDA) of applications. This tool is suitable to analyze a large amount of amount generated by an application for effective and efficient utilization of the data.

Feb 1, 2018 · Several intelligent machine learning techniques were designed and used to provide big data predictive analytics solutions. A literature survey of different machine learning techniques is provided in this paper.

Jul 23, 2024 · The use of ML algorithms for big data analytics, which extracts the high-level semantics from the valuable (meaningful) information form the data. It uses hierarchical process for efficient processing and retrieving the complex abstraction from the data.

Jan 29, 2025 · This research article presents a comprehensive framework designed to facilitate the effective integration of machine learning techniques within big data environments.

Jul 27, 2022 · Several resources claim that Mahout will scale to handle massive datasets. This article discusses and demonstrates the use of algorithms and their significant impact on Bigdata, as well as a...

Sep 15, 2016 · Big data analytics is one of the emerging technologies as it promises to provide better insights from huge and heterogeneous data. Big data analytics involves selecting the suitable big data storage and computational framework augmented by …

Jan 14, 2024 · Big data analytics consists of numerous techniques from statistical modeling to machine learning to natural language processing that use algorithms to find hidden patterns, associations, anomalies and trends within massive datasets.

Aug 14, 2020 · By feeding big data to a machine-learning algorithm, we might expect to see defined and analyzed results, like hidden patterns and analytics, that can assist in predictive modeling. For some companies, these algorithms might automate processes that were previously human-centered.

Jan 23, 2024 · Machine learning algorithms, particularly those involved in training models on substantial data, benefit greatly from the distributed and parallel processing capabilities of big data platforms. This synergy ensures that machine learning tasks can be executed efficiently, even when dealing with terabytes or petabytes of data.

May 8, 2024 · Machine learning for big data involves using sophisticated computing algorithms and statistical methods to extract information, patterns, and insights from vast and complicated datasets [1].