Machine Learning
University course, Molde University College, Department of Logistics, 2020
Teaching assistant for Machine Learning course with 100+ students at Molde University College.
Course Topics
- Supervised Learning (regression, classification)
- Unsupervised Learning (clustering, dimensionality reduction)
- Deep Learning fundamentals (neural networks, backpropagation)
- Practical applications with Python and scikit-learn
- Model evaluation and validation techniques
Responsibilities
- Leading tutorial and problem-solving sessions
- Grading assignments and projects
- Providing individual student consultations
- Assisting with lab sessions and coding exercises
- Developing course materials and examples
Key Learning Outcomes
Students gain hands-on experience with machine learning algorithms and libraries, understand the theoretical foundations of ML, and can apply these techniques to real-world problems in logistics and optimization.