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Machine Learning topics and code examples from coursework

Jupyter Notebook 100.00%
ipython-notebook keras-classification-models multivariate-regression neural-network python r-markdown r-programming time-series-forecasting univariate-regressions

worksamples_datascience's Introduction

Data Science Work Samples

Contents for this repository are intended work samples from courses and extracurricular activity that comprise my data science graduate studies journey.

Across this repository, I provide examples of supervised and unsupervised machine learning methods.

Any source code in the code notebooks that originates from other texts and data scientist contributors are consistently cited across work samples in APA formatting.

In the event a PDF is not available for work sample presentation, I provide a user-friendly version of work samples in notebook format (e.g., .Rmd and .ipynb files).

The PDF/notebooks provide key findings and visuals for quick insight. These user friendly versions only reference snippets of my wider source code relating to the reporting task.

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