Introduction to Machine Learning

Description

Introduction to machine learning. Formulation of supervised and unsupervised learning problems. Regression and classification. Data standardization and feature engineering. Loss function selection and its effect on learning. Regularization and its role in controlling complexity. Validation and overfitting. Robustness to outliers. Simple numerical implementation. Experiments on data from a wide variety of engineering and other disciplines. 

Prerequisites

• ENGR108; EE178 or CS109; CS106A or equivalent.

Notes

This course is cross listed with CME107