Lecture 2: From Semantics To Semantic-Oriented Applications

Lecture 6: Ensemble Methods

Lecture 2 Basic Concepts in Machine Learning for Language Technology

Lecture 03: Machine Learning for Language Technology - Linear Classifiers

Lecture 2: Job Opportunities

Lecture11 logistic regression

Lecture 5: Bayesian Classification

Lecture 5: Structured Prediction

Lecture 10: SVM and MIRA

Lecture 6: Hidden Variables and Expectation-Maximization

Lecture 4: Statistical Inference

Lecture 8: Decision Trees & k-Nearest Neighbors

Lecture 3 Probability Theory

Lecture 1 introduction To The Course: The Flipped Classroom

Lecture 9 Perceptron

SearchInFocus: Exploratory Study on Query Logs and Actionable Intelligence

Lecture 7: Learning from Massive Datasets

Lecture 02: Machine Learning for Language Technology - Decision Trees and Nearest Neighbors

Lecture 01: Machine Learning for Language Technology - Introduction

Lecture 4: The Weka Package