wmduggan41 / machine-learning

CS675 projects and files

Machine Learning

Learning Objectives

1. Each week consisted of an overview and a task schedule along with specific modules that delved deep into specific concepts.

2. The course curriculum progressed from basic notions such as k-Nearest Neighbors to more advanced methodologies such as Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks.

3. This systematic approach provided students with a well-rounded understanding of machine learning algorithms and techniques.

Machine Learning Methods

• Bayesian Classification
• Perceptron
• Neural Networks
• Logistic Regression
• Support Vector Machines
• Decision Trees
• Random Forests
• Boosting
• Dimensionality Reduction
• Unsupervised Learning
• Regression
• Generation of New Feature Spaces