Experiential Learning "Active" learning opportunities

This page collects together all of the “experiences” associated with individual modules.

In this site, experiences represent “active” learning opportunities, as opposed to readings, which represent “passive” learning opportunities. In many courses, readings and experiences together constitute the “assignments”.

Module: Learning conjunctions in a PAC framework

Learning conjunctions demo

Python notebook

15 Jul 11:00 PM

Module: Gaussians

The Central Limit Theorem

Simulate the Central Limit Theorem

The Central Limit Theorem 14 Jan 11:00 PM

Tour of applications

Some common application contexts for Gaussians

Common Applications for Gaussians 14 Jan 11:00 PM

Module: Linear Regression

Geometry of Linear Regression

15 Jul 11:00 PM

Significance of Features

Geometry -> Generalization

15 Jul 11:00 PM

Significance of Features: the Classical View

t- values

15 Jul 11:00 PM

Module: Single neuron networks

Python Notebook

Perceptron/Linear Regression/SVM

15 Jul 11:00 PM

Module: Support vector machines

Python Notebook

Support Vector Machines

15 Jul 11:00 PM

Module: Neural networks

Feedforward Networks

15 Jul 11:00 PM

Autoencoders

Autoencoders and SVD

15 Jul 11:00 PM