The machine learning algorithms for data science applications

Title

The machine learning algorithms for data science applications

Creator

Raj P.; Augustine D.P.; Soundarabai P.B.

Description

It is going to be data-driven insights and insights-driven decisions and actions for the total humanity. Data is being recognized as the new fuel for any individual, innovator, and institution to envisage and deliver smart and sophisticated services to its clients and customers. Data is being touted as a strategic asset for any enterprise to insightfully plan ahead and provide next-generation offerings and premium services with clarity and confidence. Newer products and solutions can be unearthed and deployed to assist humans in their everyday decisions, deals, and deeds. However, for data to be overwhelmingly beneficial, data getting garnered from multiple places have to be transitioned into information and knowledge. The process for enacting this strategically sound transformation is being continuously updated and upgraded for achieving the required optimization. That is, process excellence is gaining the attention of professors and professionals. Further on, there are scores of automated tools and enabling platforms for empowering this transition activity. Data analytics is being touted as the prime method to extract actionable insights out of data heaps. In the recent past, with the flurry of artificial intelligence (AI) algorithms, frameworks, libraries, platforms, accelerators, specialized engines, and highperformance processing architectures, AI-enabled data analytics is seeing the reality. Data science is the fast-emerging and evolving domain of study and research for finding viable ways and means that can simplify and streamline the activity of emitting hidden and useful knowledge out of data volumes. In this chapter, we want to dig deeper to spell out the strategic implications of data science technologies, tools, platforms, and infrastructures. Especially how machine learning (ML) algorithms are influencing the futuristic field of data science. The Institution of Engineering and Technology 2022.

Source

Demystifying Graph Data Science: Graph algorithms, analytics methods, platforms, databases, and use cases, pp. 345-378.

Date

2022-01-01

Publisher

Institution of Engineering and Technology

Coverage

Raj P., Edge AI Division, Reliance Jio Platforms Ltd, Bangalore, India; Augustine D.P., Department of Computer Science, Christ University, India; Soundarabai P.B., Department of Computer Science, Christ University, India

Rights

Restricted Access

Relation

ISBN: 978-183953488-1; 978-183953489-8

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1049/pbpc048e_ch16

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