A Primer with MATLAB® and Python(TM) 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
Autorentext
Erik Lee Nylen received his PhD from the Center for Neural Science at New York University, and his BSE and MS in Biomedical Engineering at the University of Iowa. He did a fellowship at Insight Data Science, and has taught at the Neural Data Science summer course at Cold Spring Harbor Laboratory. He is a patented inventor and has performed with numerous musical groups. He is currently a data scientist in New York, where he also is Executive Co-Director of The Stand, the New York City Dance Marathon.
Klappentext
A Primer with MATLAB® and Python(TM) 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
Inhalt
Part I: Foundations 1. Philosophy 2. From 0 to 0.01
Part II: Neural Data Analysis 3. Wrangling Spike Trains 4. Correlating Spike Trains 5. Analog Signals 6. Biophysical Modeling
Part III: Going Beyond the Data 7. Regression 8. Dimensionality Reduction 9. Classification and Clustering 10. Web Scraping