Neural Data Science

A Primer with MATLAB® and PythonTM present important information on the emergence of the use of Python, a more general purpose option to MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the room by providing a beginner’s introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism and enable coding versatility. Includes discussions of both MATLAB and Python in parallel Introduces the canonical data analysis cascade, standardizing the data analysis flow Presents tactics that strategically, tactically, and algorithmically help improve the organization of code

Produk Detail:

  • Author : Erik Lee Nylen
  • Publisher : Academic Press
  • Pages : 368 pages
  • ISBN : 012804098X
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKNeural Data Science

Neural Data Science

Neural Data Science
  • Author : Erik Lee Nylen,Pascal Wallisch
  • Publisher : Academic Press
  • Release : 24 February 2017
GET THIS BOOKNeural Data Science

A Primer with MATLAB® and PythonTM present important information on the emergence of the use of Python, a more general purpose option to MATLAB, the preferred computation language for scientific computing and analysis in neuroscience. This book addresses the snake in the room by providing a beginner’s introduction to the principles of computation and data analysis in neuroscience, using both Python and MATLAB, giving readers the ability to transcend platform tribalism and enable coding versatility. Includes discussions of both

Neural Data Science

Neural Data Science
  • Author : Erik Lee Nylen,Pascal Wallisch
  • Publisher : Academic Press
  • Release : 01 February 2017
GET THIS BOOKNeural Data Science

MATLAB remains the dominant language for scientific computing and analysis in neuroscience, but a more general purpose option - Python - is emerging. This book addresses the snake in the room by providing a beginner s introduction to the principles of computation and data analysis in neuroscience using both Python and MATLAB, which allows to transcend platform tribalism and enables coding versatility. Utilizing a Rosetta stone approach, including both MATLAB and Python in parallel Introducing the canonical data analysis cascade,

Studies in Neural Data Science

Studies in Neural Data Science
  • Author : Antonio Canale,Daniele Durante,Lucia Paci,Bruno Scarpa
  • Publisher : Springer
  • Release : 28 December 2018
GET THIS BOOKStudies in Neural Data Science

This volume presents a collection of peer-reviewed contributions arising from StartUp Research: a stimulating research experience in which twenty-eight early-career researchers collaborated with seven senior international professors in order to develop novel statistical methods for complex brain imaging data. During this meeting, which was held on June 25–27, 2017 in Siena (Italy), the research groups focused on recent multimodality imaging datasets measuring brain function and structure, and proposed a wide variety of methods for network analysis, spatial inference, graphical modeling, multiple testing,

Analysis of Neural Data

Analysis of Neural Data
  • Author : Robert E. Kass,Uri T. Eden,Emery N. Brown
  • Publisher : Springer
  • Release : 08 July 2014
GET THIS BOOKAnalysis of Neural Data

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among

Data Science from Scratch

Data Science from Scratch
  • Author : Joel Grus
  • Publisher : "O'Reilly Media, Inc."
  • Release : 14 April 2015
GET THIS BOOKData Science from Scratch

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core

MATLAB for Neuroscientists

MATLAB for Neuroscientists
  • Author : Pascal Wallisch,Michael E. Lusignan,Marc D. Benayoun,Tanya I. Baker,Adam Seth Dickey,Nicholas G. Hatsopoulos
  • Publisher : Academic Press
  • Release : 09 January 2014
GET THIS BOOKMATLAB for Neuroscientists

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional

Malware Data Science

Malware Data Science
  • Author : Joshua Saxe,Hillary Sanders
  • Publisher : Unknown Publisher
  • Release : 13 April 2021
GET THIS BOOKMalware Data Science

This title shows you how to apply machine learning, statistics and data visualization as you build your own detection and intelligence system. Following an overview of basic reverse engineering concepts like static and dynamic analysis, you'll learn to measure code similarities in malware samples and use machine learning frameworks like scikit-learn and Keras to build and train your own detectors.

Statistical Learning Using Neural Networks

Statistical Learning Using Neural Networks
  • Author : Basilio de Braganca Pereira,Calyampudi Radhakrishna Rao,Fabio Borges de Oliveira
  • Publisher : CRC Press
  • Release : 01 September 2020
GET THIS BOOKStatistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples. It presents a wide range of widely used statistical methodologies, applied in several research areas with Python code examples, which are available online. It is suitable for scientists and developers as well as graduate students.

Statistical Signal Processing for Neuroscience and Neurotechnology

Statistical Signal Processing for Neuroscience and Neurotechnology
  • Author : Karim G. Oweiss
  • Publisher : Academic Press
  • Release : 22 September 2010
GET THIS BOOKStatistical Signal Processing for Neuroscience and Neurotechnology

This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal

Deep Learning for Data Analytics

Deep Learning for Data Analytics
  • Author : Himansu Das,Chittaranjan Pradhan,Nilanjan Dey
  • Publisher : Academic Press
  • Release : 29 May 2020
GET THIS BOOKDeep Learning for Data Analytics

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear

Advanced Data Analysis in Neuroscience

Advanced Data Analysis in Neuroscience
  • Author : Daniel Durstewitz
  • Publisher : Springer
  • Release : 15 September 2017
GET THIS BOOKAdvanced Data Analysis in Neuroscience

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear

Python Data Science Handbook

Python Data Science Handbook
  • Author : Jake VanderPlas
  • Publisher : "O'Reilly Media, Inc."
  • Release : 21 November 2016
GET THIS BOOKPython Data Science Handbook

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and