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Have you ever wondered how internet ads are tracking you and what you have googled recently. How do you get emails from Amazon about books or movies similar to what you have recently purchased or watched? How does your Facebook page put a person's name beside their face in a photo? How does your email detect spam? How does your credit card company find an unusual transaction and notify you?
Machine learning has got the answers to all of these questions. During this class you will learn the basics of machine learning and the high-level view of a handful of algorithms to solve lots of problems. Lots of examples will be explained and you will be able to prepare the dataset and choose an appropriate algorithm for your problem by the end of the class.
Understand the difference between classification and regression problems
Understand the concept of learning algorithms
Learn the steps to pre-process a dataset and prepare it for machine learning algorithms
Realize the difference between unsupervised and supervised learning algorithms
Free datasets, tools, and packages to implement and apply the machine learning algorithms to use and challenge the skills you learned from this class
A background in computer science, programming, and/or statistics is preferred for this workshop. It is not required but you are expected to be somewhat familiar with the command line tools and how to write simple programs.
All students should complete the assigned pre-work before class and be ready to begin right away. https://www.dropbox.com/s/2t2gex4e0wxsft3/DAT%20PreWork.pdf
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