Machine Learning

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There are some uses of Conda environments here and there as well

Other works

• You can find some group projects I did with friends under the Github Organization Computer Talkers
• I wrote a Neural Network from scratch for both GPUs and CPUs here
• Notebooks my team at the Economic Development Partnership of Alabama used to analyze where students were going post-grad from Alabama colleges here

Table of Contents

Reference Notebooks
Reference Notebooks are Data Science/Machine Learning Juypter Noteboooks I was provided during my internship with the University of Alabama Department of Physics and The Economic Development Partnership of Alabama. They cover some basics such as data cleaning and Pandas, as well as intermediate topics such as model validation.

Regression Algorithms

1. Linear Regression
   1a. Dataset: Tesla Stock Data
   1b. Attempt: Predicting daily highs
   1c. Result: Model Score: $$R^2 = 0.999803851997443$$ -Highly inflated, may be overfitted here
   1d. Usefulness: Little to no usefulness due to the enigmatic nature of the stock market

Datasets

Kaggle

References

Andrew Ng x Standford University Coursera Machine Learning Course

Reference Notebooks