Welcome to the Statistical Machine Learning (SML) course! This repository contains Jupyter notebooks and labs designed for a 55-minute class session each.
Machine Learning (ML) is a dynamic field at the crossroads of data science, mathematics, statistics, and computer science. It involves techniques that allow machines to learn from data and improve over time. This course integrates ML algorithms with statistical thinking. For details on covered material, see the overview notebook.
- Overview
- Data Representation
- Lab 1: Data Collection
- Worksheet for Lab 1
- Multiple Linear Regression
- Performance Metrics for MLR
- Worksheet for MLR Performance Metrics
For further reading, we recommend:
Feel free to explore the notebooks and labs, and check back for new content!