Webinar 6: Supervised Learning

In this session, we will explore the fundamentals of supervised learning methods in machine learning, including Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines (SVM), and K-Nearest Neighbors (KNN). Each method will be illustrated with real-world examples to demonstrate their practical applications. Attendees will gain a solid understanding of how these algorithms work, their use cases, and how to implement them effectively in Python. By the end of the session, participants will be equipped with the knowledge to apply these supervised learning techniques to solve various predictive modeling problems.

Dr. Nouf AlShenaifi is a lecturer, researcher, and PhD candidate at King Saud University, specializing in Artificial Intelligence, machine learning, and data science. Her research focuses on Natural Language Processing methods. She actively engages in innovative research, with work published in prestigious journals and presented at international conferences, reflecting her commitment to advancing the field of Artificial Intelligence.