Machine Learning Coursework

Overview

• What It Is: This is a collection of projects and assignments from various machine learning courses, including the UCF's Master of Science in FinTech program.
• Goal: The goal is to showcase my understanding of machine learning concepts and applications in finance and technology.

Key Achievements & Features

1. Python Package Essentials
   • Packages include NumPy, Pandas, Matplotlib, and Scikit-Learn.
   • Used for data manipulation, visualization, and machine learning model building.
2. Regression & Classification Models
   • Built linear regression models to predict stock prices.
   • Implemented classification models to predict if a sales call to a banker for a term deposit subscription would be successful would end in a sale or not.
   • Used clustering algorithms to identify patterns in stock market data.

Technologies & Skills Demonstrated

• Python
• Jupyter Notebooks
• Machine Learning Libraries (NumPy, Pandas, Matplotlib, Scikit-Learn)
• Regression & Classification Models
• Clustering Algorithms

Big-Picture Vision

• Evidence-Based Decision Making: Through applied mathematics, statistics and machine learning, the projects demonstrate the ability to make data-driven decisions.
• Future Research Directions: This project sets the foundation for my AI career path, with future applications in predictive analytics, algorithmic trading, and more.