Machine Learning & Optimization Instructor — Online/Remote Teaching
Prompt + Response Writing (SFT)Taught supervised learning, gradient descent, loss functions, evaluation metrics, and optimization methods with a strong emphasis on reproducible Python experimentation. Produced structured lessons, examples, and explanations that connect mathematical concepts to practical workflows for model building, debugging, and evaluation. Guided learners through algorithmic thinking and implementation details to support consistent learning and assessment of ML understanding. • Developed lesson materials and technical explanations for supervised learning and optimization reasoning. • Helped learners practice debugging and reproducible experimentation in Python-based workflows. • Trained understanding of feature engineering and evaluation metric selection for model assessment. • Supported implementation-focused learning of ML reasoning and algorithmic detail.