CS559_Machine-Learning-Fundamentals-Applications

General information

• Course Title: Machine Learning: Fundamentals and Applications

• Course Code: CS 559

• Academic Level: Graduate

• Instructor: Tian Han

• Department: Computer Science

• University: Stevens Institute of Technology

• Course Period: Fall Semester in 2023 (Sep 2023 - Dec 2023)

Course description

In this course we will talk about the foundational principles that drive machine learning applications and practice implementing machine learning algorithms. Specific topics include supervised learning, unsupervised learning, neural networks, and graphical models. The main goal of the course is to equip you with the tools to tackle new ML problems you might encounter in life.

Skills

• Programming: Python
• Libraries: Tensorflow, Keras
• Software: Jupyter Notebook, Google Colab
• ML Skills: Introduction to Probability & Linear Algebra, Decision Theory, Maximum LIkelihood Estimation & Bayesian estimation, Linear Model, Linear Discriminant function, Perceptron, Fisher Linear Discriminant, PCA, Non-parametric Learning, Clustering, EM, GMM, EM and Latent Variable Model, Probabilistic Graphical Model, Bayesian Network, Neural Network, Support Vector Machine, Decision Tree and Boosting