Machine Learning with March Madness

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Machine Learning with March Madness-0
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60 min
Group Course
Machine Learning with March Madness-0

Use machine learning models to make predictions about the outcome of games in the NCAA march madness matches.

What you'll learn

Have you ever wanted to learn machine learning using real-world data? Our online class is perfect for you! We use the March Madness dataset to give you a hands-on introduction to machine learning. You'll explore the data, develop models to predict winning teams, and understand player evaluations. Our program gives you the knowledge and confidence to build your own algorithms for any situation.

This class is perfect for

This class is perfect for anyone- those who want to sharpen their machine-learning skills; or want don't know much but are curious about machine learning; or want to improve their NCAA bracketology...

Listing availability

(Timezone: Etc/UTC)

Jan 01-07, 1970

What to bring

You need a computer or laptop, or...
Group sessionUp to 10 seats
Group sessionUp to 10 seats

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Learn ,data-science.deep-learning-and-machine-learning, with Uohna T | Amphy
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Uohna Thiessen, Ph.D.

Your teacher

Uohna Thiessen, Ph.D., is a consultant data scientist at Accenture in AdTech practice, working with one of the top-performing corporate tech companies (MAANG). She teaches statistics, quantitative analysis, data science, and machine learning at various U.S. institutions, including the California Institute of Technology and the Flatiron School in NYC. Machine learning models she developed in sectors such as medicine, advertising, and financial technology were designed in R, Python, and SPSS, as well as MS Azure, Google TensorFlow, and Apache PySpark. Uohna holds a Ph.D. in Epidemiology (biostatistics concentration) from Walden University and a B.Sc in biochemistry from Oakwood University. She is certified in Cloud computing and machine learning engineering through Google (GCP) and Microsoft (Azure). Dr. Uohna Thiessen is a data scientist and data science educator whose mission is to provide access to data science education to as many people as possible.

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