Foundations of data science for engineering problem solving / Parikshit Narendra Mahalle, Gitanjali Rahul Shinde, Priya Dudhale Pise, Jyoti Yogesh Deshmukh.
2022
TA345 .M35 2022
Linked e-resources
Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Foundations of data science for engineering problem solving / Parikshit Narendra Mahalle, Gitanjali Rahul Shinde, Priya Dudhale Pise, Jyoti Yogesh Deshmukh.
ISBN
9789811651601 (electronic bk.)
9811651604 (electronic bk.)
9789811651595
9811651590
9811651604 (electronic bk.)
9789811651595
9811651590
Published
Singapore : Springer, [2022]
Copyright
©2022
Language
English
Description
1 online resource : illustrations (chiefly color)
Other Standard Identifiers
10.1007/978-981-16-5160-1 doi
Call Number
TA345 .M35 2022
Dewey Decimal Classification
620.001/5
Summary
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed August 30, 2021).
Added Author
Shinde, Gitanjali Rahul, 1983- author.
Pise, Priya Dudhale, author.
Deshmukh, Jyoti Yogesh, author.
Pise, Priya Dudhale, author.
Deshmukh, Jyoti Yogesh, author.
Series
Studies in big data ; v. 94. 2197-6511
Available in Other Form
Print version: 9789811651595
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
All Resources
Table of Contents
Introduction to Data Science
Data Collection and Preparation
Data Analysis and Machine learning Algorithms
Data Visualization Tools and Data Modelling
Data Science in Information, Communication and Technology
Data Science in Civil & Mechanical Engineering
Data Science in Clinical Decision System
Conclusions.
Data Collection and Preparation
Data Analysis and Machine learning Algorithms
Data Visualization Tools and Data Modelling
Data Science in Information, Communication and Technology
Data Science in Civil & Mechanical Engineering
Data Science in Clinical Decision System
Conclusions.