Machine Learning Project

Lazaridis School of Business & Economics at Wilfrid Laurier University

In this project, I had the opportunity to apply my knowledge and skills in machine learning to a real-world problem: predicting flight delays. By conducting exploratory data analysis and implementing various machine learning models, I was able to analyze the data and make informed predictions about the likelihood of flight delays.

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As part of the machine learning project, I had the opportunity to work with a variety of machine learning models. These models included linear and logistic regression, which are commonly used for predicting continuous and binary outcomes, respectively.

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I also worked with regression trees, which are decision tree models that can be used for both classification and regression tasks. These models are particularly useful for understanding the underlying relationships between variables and can be easily interpreted and visualized.

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Finally, I utilized support vector machine (SVM) models, which are a type of supervised learning algorithm that can be used for both classification and regression tasks. SVM models work by finding the hyperplane in a high-dimensional space that maximally separates the different classes. These models are particularly effective when the data is not linearly separable and can provide excellent results on a variety of tasks.

These machine learning models allowed me to gain a deep understanding of the various techniques and approaches that can be used for predicting outcomes and making informed decisions based on data.

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One of the key challenges in this project was effectively communicating the results of my analysis to a non-technical audience. To this end, I developed a convincing and persuasive project proposal outlining the objectives and methods of the study, and formulated and analyzed the business problem in a quantitative manner. By presenting the results of my quantitative analysis and arguing for a particular course of action based on the findings, I was able to effectively communicate the results of my work to my peers and instructors.

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Overall, this project allowed me to develop and strengthen my skills in machine learning, data analysis, and problem-solving, and provided me with valuable hands-on experience applying advanced analytic techniques.