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Application Of Big Data Technology, Text Classification, And Azure Machine Learning For Financial Risk Management Using Data Science Methodology, Oluwaseyi A. Ijogun
Application Of Big Data Technology, Text Classification, And Azure Machine Learning For Financial Risk Management Using Data Science Methodology, Oluwaseyi A. Ijogun
Electronic Theses and Dissertations
Data science plays a crucial role in enabling organizations to optimize data-driven opportunities within financial risk management. It involves identifying, assessing, and mitigating risks, ultimately safeguarding investments, reducing uncertainty, ensuring regulatory compliance, enhancing decision-making, and fostering long-term sustainability. This thesis explores three facets of Data Science projects: enhancing customer understanding, fraud prevention, and predictive analysis, with the goal of improving existing tools and enabling more informed decision-making. The first project examined leveraged big data technologies, such as Hadoop and Spark, to enhance financial risk management by accurately predicting loan defaulters and their repayment likelihood. In the second project, we investigated …
Cloud-Based Machine Learning And Sentiment Analysis, Emmanuel C. Opara
Cloud-Based Machine Learning And Sentiment Analysis, Emmanuel C. Opara
Electronic Theses and Dissertations
The role of a Data Scientist is becoming increasingly ubiquitous as companies and institutions see the need to gain additional insights and information from data to make better decisions to improve the quality-of-service delivery to customers. This thesis document contains three aspects of data science projects aimed at improving tools and techniques used in analyzing and evaluating data. The first research study involved the use of a standard cybersecurity dataset and cloud-based auto-machine learning algorithms were applied to detect vulnerabilities in the network traffic data. The performance of the algorithms was measured and compared using standard evaluation metrics. The second …
Regression Tree Construction For Reinforcement Learning Problems With A General Action Space, Anthony S. Bush Jr
Regression Tree Construction For Reinforcement Learning Problems With A General Action Space, Anthony S. Bush Jr
Electronic Theses and Dissertations
Part of the implementation of Reinforcement Learning is constructing a regression of values against states and actions and using that regression model to optimize over actions for a given state. One such common regression technique is that of a decision tree; or in the case of continuous input, a regression tree. In such a case, we fix the states and optimize over actions; however, standard regression trees do not easily optimize over a subset of the input variables\cite{Card1993}. The technique we propose in this thesis is a hybrid of regression trees and kernel regression. First, a regression tree splits over …
Developing Computer Vision Technology To Automate Pitch Analysis In Baseball., Mahdi Moalla
Developing Computer Vision Technology To Automate Pitch Analysis In Baseball., Mahdi Moalla
Electronic Theses and Dissertations
Lokator is a baseball training system designed to document pitch location while teaching pitch command, selection and sequencing. It is composed of a pitching target and a smartphone app. The target is divided into a set of zones to identify the pitch location. The main limitation of the current system is its reliance on the user's feedback. After each throw, the pitcher or the coach needs to identify and report the target's zone that was hit by the ball by just relying on the naked eye. The purpose of this thesis is to investigate the possibility of using computer vision …