Data Science for Neuroimaging: An Introduction by Ariel Rokem (.PDF)

File Size: 12.6 MB

Data Science for Neuroimaging: An Introduction by Ariel Rokem, Tal Yarkoni
Requirements: .PDF reader, 12.6 MB
Overview: Data Science methods and tools―including programming, data management, visualization, and Machine Learning―and their application to neuroimaging research. 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. Note that this book is not meant to be a general introduction to programming. We are going to spend some time introducing the reader to programming in the Python programming language (starting in chapter 5; we will also explain specifically why we chose the Python programming language for this book), but for a gentler introduction to programming, we will refer you to other resources. There are a few different Python software libraries that visualize data. We will start with a library called Matplotlib.
Genre: Non-Fiction > Tech & Devices

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