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NEURAL DATA SCIENCE. A PRIMER WITH MATLAB® AND PYTHON
Título:
NEURAL DATA SCIENCE. A PRIMER WITH MATLAB® AND PYTHON
Subtítulo:
Autor:
NYLEN, E
Editorial:
ACADEMIC PRESS
Año de edición:
2017
Materia
MATLAB
ISBN:
978-0-12-804043-0
Páginas:
368
45,95 €

 

Sinopsis

Description
A Primer with MATLAB® and PythonT 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.

Key Features
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
Readership
Students, researchers and instructors in Systems, Cognitive and Behavioral Neuroscience, and Cognitive Psychology



Table of Contents
Part I: Foundations

Chapter 1. Philosophy

Abstract
What Is Data Science?
What Is Neural Data Science?
How Is Neural Data Science Different From Computational Neuroscience?
Data as Seen by Data Scientists Versus Data Seen by Neural Data Scientists
What Is a Neural Data Scientist?
Why Do I Need to be Able to Write Computer Code?
What Is Neural Data?
Can We Just Add "Neuroö to the Front of Anything?
Why Python?
Why MATLAB?
Why Not C/C++/R/Julia/Haskill/Java/Javascript/OCaml/Perl/Pascal/Fortran/Ruby/Groovy/Scala/etc.?
What Is Industrial Data Science? How Is It Different From Engineering?
Chapter 2. From 0 to 0.01

Abstract
What Is the Goal of This Chapter?
How Do I Get Started Coding?
What's the Command Line? What's the Environment?
How Are Python and MATLAB Different?
How Do I Display Something on the Screen?
How Do I Do Arithmetic in Python or MATLAB?
How Do I Input Exponents in Python and MATLAB?
What Is the Role of Blank Space in Writing Code, If Any?
What Is the Order of Operations in Python and MATLAB?
What Are Functions?
What Are Python Packages? What Are MATLAB Toolboxes? Are These Different From Libraries?
How Do I Get Help?
What Are Variables?
How Can I Access or Display What Is Contained in a Given Variable?
What Is "ansö in MATLAB?
What Can We Call Our Variables?
What Is a Vector? How Do I Store a Vector in POM?
How Do I Calculate the Sum and Mean of All Values in a Vector?
We Need to Talk About the Echo
How Do I Calculate the Length of a Vector?
What Are Matrices, What Are Arrays?
Back to Vectors: How to Vectorize a Matrix?
What Can We Do With All of This?
The Find Function
Adding Matrices and Dealing With Holes in Arrays
What Is a Normal Distribution? How Do We Draw From One, How Do We Plot One With POM?
How Do I Plot Something More Meaningful?
How Do I Save What I'm Working On so That I Can Load It Again Later?
Part II: Neural Data Analysis

Chapter 3. Wrangling Spike Trains

Abstract
Questions We Did Not Address
Chapter 4. Correlating Spike Trains

Abstract
Chapter 5. Analog Signals

Abstract
Chapter 6. Biophysical Modeling

Abstract
Biophysical Properties of Neurons
Modeling
Why Use Simulations?
Why Object-Oriented Programming?
Python Is Inherently Object-Oriented: How Does MATLAB Implement These Things?
Creating theclass Neuron
Modeling the Response Properties of This Neuron
Part III: Going Beyond the Data

Chapter 7. Regression

Abstract
Describing the Relation Between Synaptic Potentials and Spikes
Chapter 8. Dimensionality Reduction

Abstract
Calculating the Covariance Matrix Between Variables
Factor Extraction as an Axis Rotation
Determining the Number of Factors
Interpreting the Meaning of Factors
Determining the Factor Values of the Original Variables
Chapter 9. Classification and Clustering

Abstract
Predictions, Validation, and Crossvalidation
Clustering
Chapter 10. Web Scraping

Abstract
What Lies Beyond 1?
Appendix A. MATLAB to Python (Table of Equivalences)

Comments
Blankspace
Loops
Exponents
Lists and Cells
Indexing
Importing Packages Versus Default Packages
Random Number Generation
Numerical Types
Appendix B. Frequently Made Mistakes

Appendix C. Practical Considerations, Technical Issues, Tips and Tricks

Package Installation
Python List Comprehensions
Python Lists Versus Numpy Arrays
Text Editors, The Command Line, How to Go between Sublime and the Terminal
Python on Windows
Jupyter: Using It and Its Great Functions
The Biggest Differences Between Python 2 and 3
Conventions in Python
MATLAB Tips and Tricks
Vectorization
Practical Considerations
Glossary (Including Additional Python and MATLAB Packages and Examples)