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data-science.html
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<!DOCTYPE html>
<html lang="en">
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<meta charset="utf-8">
<meta content="width=device-width, initial-scale=1.0" name="viewport">
<title>Julian Wyatt</title>
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<ul>
<li class="active"><a href="./">Home</a></li>
<li><a href="./#about">About</a></li>
<li><a href="./#resume">Resume</a></li>
<li><a href="./#portfolio">Portfolio</a></li>
<li><a href="./#contact">Contact</a></li>
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<h2 >Data Science and Research Experience</h2>
<p>
During my second year of university, I was exposed to modern data science and research methods which have highlighted a likely career avenue for myself.
Firstly, I had to research and write a report about non-local means denoising, which included comparisons to similar denoising algorithms, explanations of parameters as well as modifications on the original algorithm.
During this project, I was introduced to the OpenCV library which is paramount in the world of computer vision. Additionally, later in the year I experienced my first machine learning project. I was tasked to develop a model to predict the end of year grades based on the Open University Learning Analytics Dataset (OULAD) and write a report explaining and describing my outcomes. My highest performing models were a random forest classifier & a logistic regression model. These achieved a 2-class accuracy of 0.96 and 0.92 respectively.
<br>
<b>Libraries & Technologies used:</b> Python, Numpy, Seaborn, Scikit-Learn, Pandas, Hyperopt libraries, OpenCV, LaTeX
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<i class="icofont-rounded-right"></i>The machine learning source code is available here:
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<i class="icofont-rounded-right"></i>To view the ML analysis and paper, please click here:
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<i class="icofont-rounded-right"></i>To view the Image Processing paper, please click here:
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<img src="assets/img/portfolio/alley-highNoise.png" style="max-height: 600px;object-fit: contain;" alt="">
High noise image of alley
</div>
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<img src="assets/img/portfolio/IPalley-gaussian,2.png" style="max-height: 600px;object-fit: contain;" alt="">
High noise image of alley denoised with gaussian
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<img src="assets/img/portfolio/MLLogisticRegression_2_class_model_against_summative.png" style="max-height: 600px;object-fit: contain;" alt="">
Logistic regression estimation over pass/fail grades
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<img src="assets/img/portfolio/MLdataset.png" style="max-height: 600px;object-fit: contain;" alt="">
OULAD Schema
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<img src="assets/img/portfolio/MLAccuracy_against_iteration2.png" style="max-height: 600px;object-fit: contain;" alt="">
Accuracy against epoch
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<h3>Julian Wyatt</h3>
<p>If you wish to contact me to ask any questions about any of my work or to view my work, please use the social links below.<br> I would love to hear from you!</p>
<p><strong>Email:</strong> [email protected]</p>
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