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This book addresses the growing need for machine learning and data mining in neuroscience. The book is replete with fully working machine learning code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook.
List of contents
1. Basic Linear Algebra. 2. Overview of Statistics. 3. Introduction to Python Programming. 4. More with Python. 5. General Neuroanatomy and physiology. 6. Cellular neuroscience. 7. Neurological disorders. 8. Introduction to Computational Neuroscience. 9. Overview of machine learning. 10. Artificial Neural Networks. 11. More with ANN. 12. K Means Clustering. 13. K Nearest Neighbors. 14. Self Organizing Maps.
About the author
Dr. Chuck Easttom is the author of 32 books. He is an inventor with 22 computer science patents. He holds a Doctor of Science in cybersecurity, a Ph.D. in Nanotechnology, and a Ph.D. in computer science as well as three master's degrees (one in applied computer science, one in education, and one in systems engineering). He is a senior member of both the IEEE and the ACM. He is also a Distinguished Speaker of the ACM and a Distinguished Visitor of the IEEE. He has been active in the IEEE Brain Computer Interface Standards and is a member of the IEEE Engineering in Medicine and Biology Society.
Summary
This book addresses the growing need for machine learning and data mining in neuroscience. The book is replete with fully working machine learning code. It also contains lab assignments and quizzes, making it appropriate for use as a textbook.
