Foundations of Machine Learning Lab
Introduction to Machine Learning in Pharmaceutical Sciences (BP301T) · Semester 3 · Unit 1: Foundations of Machine Learning
Walk through learning types, feature/label framing, splitting, training, testing, evaluation, and the overfitting boundary.
What this unit covers
Artificial Intelligence, Machine Learning, and Data Science use different scopes. A foundational ML workflow frames features and labels, separates training and testing data, and considers overfitting, underfitting, bias–variance trade-off, and the learning type before any result is interpreted.
Apply it
Map a fictional formulation-learning problem into features, a label, a learning type, and a train/test split; then state one overfitting safeguard.
How this lab works
A visible browser-native teaching interaction updates illustrative states, scores, or visual summaries from authored values.
Data used
Fictional or browser-generated teaching inputs; no patient, proprietary manufacturing, or clinical-record data.
Limits
Educational simulation only. Outputs are not clinical advice, patient-specific predictions, release specifications, regulatory decisions, or professional competency evidence.