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Springer Foundations of Data Science for Engineering Problems

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Description

Foundations of Data Science for Engineering Problem Solving provides a comprehensive guide for addressing complex engineering challenges through data-driven methods. Part of the Studies in Big Data series, this book serves as a practical resource for implementing data science models in real-time business expansions and multidisciplinary environments. Readers will learn to use AI algorithms for making future predictions and informed decisions. The text covers machine learning and optimization techniques to provide strong insights for novice users. As data sources vary across different use cases, this book addresses the need for source-specific models to handle big data effectively in the real world.

Key Features

This Springer publication offers essential information for solving engineering problems across various disciplines.

Learn to implement AI algorithms to assist with future predictions and decision-making processes.

The book provides strong insights into machine learning and optimization techniques for novice users.

Address the needs of the big data era by studying data science problems from a multidisciplinary perspective.

Develop source-specific data science models designed for real-world use cases and diverse data types.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
23 August 2022
Listed Since
01 August 2022

Barcode

No barcode data available

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