Introduction - CSC 411 CSC D11 Introduction to Machine...

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CSC 411 / CSC D11 Introduction to Machine Learning 1 Introduction to Machine Learning Machine learning is a set of tools that, broadly speaking, allow us to “teach” computers how to perform tasks by providing examples of how they should be done. For example, suppose we wish to write a program to distinguish between valid email messages and unwanted spam. We could try to write a set of simple rules, for example, flagging messages that contain certain features (such as the word “viagra” or obviously-fake headers). However, writing rules to accurately distinguish which text is valid can actually be quite difficult to do well, resulting either in many missed spam messages, or, worse, many lost emails. Worse, the spammers will actively adjust the way they send spam in order to trick these strategies (e.g., writing “[email protected]@”). Writing effective rules — and keeping them up-to-date — quickly becomes an insurmountable task. Fortunately, machine learning has provided a solution. Modern spam filters are “learned” from examples: we provide the learning algorithm with example emails which we have manually labeled as “ham” (valid email) or “spam” (unwanted email), and the algorithms learn to distinguish between them automatically. Machine learning is a diverse and exciting field, and there are multiple ways of defining it: 1. The Artifical Intelligence View. Learning is central to human knowledge and intelligence, and, likewise, it is also essential for building intelligent machines. Years of effort in AI has shown that trying to build intelligent computers by programming all the rules cannot be done; automatic learning is crucial. For example, we humans are not born with the ability to understand language — we learn it — and it makes sense to try to have computers learn language instead of trying to program it all it. 2.
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Introduction - CSC 411 CSC D11 Introduction to Machine...

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