BP301T · Semester 3 · B.Pharm
Unit I — Foundations of Machine Learning
Introduction to Machine Learning in Pharmaceutical Sciences
This study page introduces Foundations of Machine Learning in Introduction to Machine Learning in Pharmaceutical Sciences (BP301T), B.Pharm Semester 3. Read the selected definitions and short notes below, then download the full unit PDF.
Topics in this unit
- Definition and scope of Artificial Intelligence, Machine Learning, and Data Science
- Supervised, unsupervised, and reinforcement learning
- Features, labels, training and testing data, model building, and prediction
- Train-test split, overfitting, underfitting, bias-variance trade-off, and the basic ML workflow
Definitions and short notes
Selected extracts from this unit’s notes. Download the full PDF below for the remaining topics and examples.
Artificial Intelligence (AI)
Artificial Intelligence is the science of making machines do tasks that normally need human intelligence — for example, recognizing a disease from an X-ray, reading a prescription, or answering a patient's question. "Artificial" means man-made; "intelligence" means the ability to learn and decide.
Unit PDF · page 2
Machine Learning (ML)
Machine Learning is a branch of AI in which the computer learns patterns from data instead of being given fixed rules by a programmer. In ordinary programming, a human writes the rule: "if temperature is above 38°C, then fever." In machine learning, the computer studies thousands of past records and discovers the rule by itself: "patients with these symptoms usually have this disease."
Unit PDF · page 2
Download notes
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For education and exam preparation only, not medical advice or current regulatory guidance.