Data science for neuroimaging: an introduction

By:

Rokem, Ariel

Contributor(s):

Yarkoni, Tal [Co-author]

Publication details: Princeton: Princeton University Press, 2024.Description: xiv, 377p.: ill.; pbk.: 25 cmISBN:

9780691222752

Subject(s):

DDC classification:

616.804754 ROK

Summary: As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to data science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book explains such elements of data science as programming, data management, visualization, and machine learning, and describes their application to neuroimaging. Readers will come away with broadly relevant data science skills that they can easily translate to their own questions. • Fills the need for an authoritative resource on data science for neuroimaging researchers • Strong emphasis on programming • Provides extensive code examples written in the Python programming language • Draws on openly available neuroimaging datasets for examples • Written entirely in the Jupyter notebook format, so the code examples can be executed, modified, and re-executed as part of the learning process https://press.princeton.edu/books/hardcover/9780691222738/data-science-for-neuroimaging

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
Books	IIT Gandhinagar	General	616.804754 ROK (Browse shelf(Opens below))	1	Available	034452

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Previous	616.804754 BEE Introduction to human neuroimaging	616.804754 FIL Oxford textbook of neuroimaging	616.804754 OMB Handbook of neuroimaging data analysis	616.804754 ROK Data science for neuroimaging: an introduction	616.804754 ULU FMRI: from nuclear spins to brain functions	616.8047547 HAN Brain signal analysis: advances in neuroelectric and neuromagnetic methods	616.8047547 LUC Introduction to the event-related potential technique, 2nd ed.	Next

Includes Bibliography, and Index.

As neuroimaging turns toward data-intensive discovery, researchers in the field must learn to access, manage, and analyze datasets at unprecedented scales. Concerns about reproducibility and increased rigor in reporting of scientific results also demand higher standards of computational practice. This book offers neuroimaging researchers an introduction to data science, presenting methods, tools, and approaches that facilitate automated, reproducible, and scalable analysis and understanding of data. Through guided, hands-on explorations of openly available neuroimaging datasets, the book explains such elements of data science as programming, data management, visualization, and machine learning, and describes their application to neuroimaging. Readers will come away with broadly relevant data science skills that they can easily translate to their own questions.

• Fills the need for an authoritative resource on data science for neuroimaging researchers
• Strong emphasis on programming
• Provides extensive code examples written in the Python programming language
• Draws on openly available neuroimaging datasets for examples
• Written entirely in the Jupyter notebook format, so the code examples can be executed, modified, and re-executed as part of the learning process

https://press.princeton.edu/books/hardcover/9780691222738/data-science-for-neuroimaging

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