- π Iβm currently working on mastering my understanding of statistics, the model development lifecycle, and professional pythonic development by practicing tidying data, creating models, evaluating models, improving model performance, and practicing audio compression through the Neuralink Compression Challenge.
- π± Iβm currently learning Python Programming and the human mind through An Introduction to Python by Bill Lubanovic and Nancy Kanwisher's 9.13 The Human Brain course through MIT OpenCourseWare.
- π― Iβm looking to collaborate with Neuroscientists, Data Scientists, Statisticians, Engineers, & Product Managers.
- π€ Iβm looking for help with understanding the biological mechanisms of memory and learning.
- π¬ Ask me about my current favorite course: MIT's 9.13 The Human Brain, my work with IBM & Clemson University, or my volunteer work with the Helping Hands Charity.
- π« How to reach me [Email is best & available upon request]:
- β‘ Fun fact: I was an actor in a variety of plays with the Charleston Stage Company.
Highlights
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kernel-brain-data
kernel-brain-data PublicThis is a repository to train a neural network to detect laughter.
Jupyter Notebook
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data-structures-and-algorithms
data-structures-and-algorithms PublicData Structures and Algorithms C++ Certificate with Tests and Solutions to Leetcode Exercises
C++
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Neuralink-Compression-Challenge
Neuralink-Compression-Challenge PublicThis is my solution to the Neuralink Compression Challenge to compress a sample of neural audio losslessly written in python. It includes modules to encode and decode as well as a suite of tests.
Jupyter Notebook 3
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Decoding-EEG-during-AO-MI-ME
Decoding-EEG-during-AO-MI-ME PublicForked from IoBT-VISTEC/Decoding-EEG-during-AO-MI-ME
Improvement upon the IEEE Sensors Journal research of decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting.
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An-Introduction-To-Statistical-Learning-With-Applications-In-R-Second-Edition
An-Introduction-To-Statistical-Learning-With-Applications-In-R-Second-Edition PublicMy study of "An Introduction to Statistical Learning with Applications in R Second Edition" by Gareth James, Daniela Witten, Trevor Hastie, & Robert Tibshirani
HTML 1
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R-For-Data-Science
R-For-Data-Science PublicMy self-study of the well-written book "R for Data Science" by Hadley Wickham & Garret Grolemund.
TeX
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