Essential Concepts of Machine Learning
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Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. This lesson introduces some key algorithms of machine learning, including classification and decision trees, through visual examples and sample code.
Objectives
Upon completion of this lesson, you will be able to
Upon completion of this lesson, you will be able to
- define machine learning
- identify areas of application
- explain automated classification
- list key machine learning algorithms
- apply and tune kNN algorithm to classification and prediction tasks
Required Readings
- Flach, Peter (2016). Prologue: A Machine Learning Sampler. Excerpt from Machine Learning: The Art and Science of Algorithms that Make Sense of Data, Cambridge University Press.
- McCrea, Nick. An Introduction to Machine Learning Theory and Its Applications: A Visual Tutorial with Examples.
- Lantz, B. (2016). Machine Learning with R. Chapter 3 on kNN.
Example Code & Data Sets
Supporting Software & Tools
- TBD