MTH221-Fundamentals of Machine Learning
About The Course
Course Description: The "Fundamentals of Machine Learning" course is designed to provide a comprehensive introduction to the core concepts, techniques, and algorithms of machine learning. The course will cover a wide range of topics, including supervised learning, unsupervised learning, model evaluation, and model selection. Students will learn about various machine learning algorithms such as linear regression, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, and neural networks. The course will also include hands-on programming exercises and projects to provide practical experience in implementing and evaluating machine learning algorithms.
- Name: MTH221 Fundamentals of Machine Learning
- Offered By: Middle East Technical University
- Lecturer: BATUHAN BARDAK
- Course website: METU Course Catalog
Skills and Insights Gained
I am taking the course this semester. We are currently exploring the foundational concepts and algorithms that form the backbone of machine learning. This includes studying supervised and unsupervised learning methods and working through key algorithms like linear and logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, and neural networks.
I'm also learning about important aspects of model evaluation and selection, which are essential for improving machine learning models. The course includes hands-on programming exercises, providing me with practical experience as I implement and test various algorithms, helping to reinforce the theoretical knowledge gained.