Lecture 2: From Semantics To Semantic-Oriented Applications
Lecture 6: Ensemble Methods
Lecture 03: Machine Learning for Language Technology - Linear Classifiers
Lecture 2 Basic Concepts in Machine Learning for Language Technology
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