Lecture 1: Introduction – Machine Learning for Language Technology

What Is Machine Learning? Machine learning is programming computers to optimize a performance criterion using example data or past experience. We have a model defined up to some parameters, and learning is the execution of a computer program to optimize the parameters of the model using the training data or past experience. The model may be predictive to make predictions in the future, or descriptive to gain knowledge from data, or both. Machine learning uses the theory of statistics in building mathematical models, because the core task is making inference from a sample. (Alpaydin, 2010)
In this lecture, we discuss supervised learning starting from the simplest case. We introduce the concepts of: Margin, Noise, and Bias.

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