Lecture IV - Supervised Learning
The goal for this lecture is to familiarize the students with some of the basic supervised machine learning algorithms and the care that must be taken in their application applications. In particular:
Sept 7, 2017 - 12:15-13:10
- Regression vs Classification
- Overfitting
- Bias-Variance Tradeoff
- K-Nearest Neighbors
- Validation dataset
- Perceptron
- Activation Functions
- Back Propagation
- Support Vector Machines
By the end of the lecture the students will understand some of the fundamental supervised machine learning algorithms.