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Introduction to Machine Learning in Python with Alyssa Batula

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This class will help you get started working with machine learning in Python, starting with an overview of what machine learning is as well as what it can and cannot do. We will use Jupyter notebooks and the scikit-learn library to explore how data is used for machine learning and examples of three types of algorithms: classification, regression, and clustering. At the end of this course, you will be able to run a simple algorithm on a dataset and have resources for more in-depth learning on how these algorithms work.

Prerequisites: Basic Python programming (including the use of functions)

Software Needed: Python 3 (2 might work, but I can't guarantee it) and the following libraries: scikit-learn, numpy/scipy, matplotlib

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