Question Answering

This project will involve the implementation of artificial intelligence in order to answer questions posed to a computer which are written in natural language. Once a certain question is asked, the computer will answer it according to a pre-recorded database. If, however, the computer is incorrect in its response, or is not thorough enough, the [...]

Lab 1 – Thomas Burns

Boosting (The Non-Wiki Version)

Intro to Boosting Boosting is a simple concept which coincidentally prides itself on simplicity. The idea can be found in looking at the very root principle of artificial intelligence itself – that is, a machine learning to make accurate predictions based on past observations. Boosting follows this exact concept. By implementing several “weak” or “base” learners [...]


Tommy Burns. Boosting is a machine learning meta-algorithm for performing supervised learning. Boosting is based on the question posed by Kearns: can a set of weak learners create a single strong learner? A weak learner is a classifier only slightly correlated with true classification (it can label examples better than random guessing). In contrast, a strong learner [...]