ChatGPT Machine Learning Unleashed

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60 min
Group Class
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Learn how to generate a machine learning model for heart disease data and use Gradio to develop an app based on the model. Predictive models, feature engineering, model evaluation and optimization, web development, and deploying the model as an app.


What you'll learn

This course teaches students how to generate a machine-learning model for heart disease data and use Gradio to develop an app based on the model. Through this course, students will learn about predictive models, feature engineering, model evaluation and optimization, web development, and deploying the model as an app. By the end of the course, students will have a working app that can be used to predict heart disease. Through this course, students will learn about predictive models, fe... 
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What to bring

Computer or laptop, internet access, and a ChatGPT account.
Tickets
Group sessionUp to 50 seats
Group sessionUp to 50 seats

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Learn ,data-science.deep-learning-and-machine-learning,data-science.chatgpt, 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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