Tidymodels in R: Building tidy machine learning models

This guided project aims to empower data professionals to build tidy machine-learning models in R. In this 2-hour project-based course, you will be working in the context of a real-world scenario as

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Last updated Thu, 01-Jan-1970
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Course overview
This guided project aims to empower data professionals to build tidy machine-learning models in R. In this 2-hour project-based course, you will be working in the context of a real-world scenario as part of a data-science team tasked with reducing hospital readmissions for a leading healthcare organization. Through hands-on practice, you’ll learn to preprocess clinical data and train and evaluate machine learning models. By the end of this learning experience, you'll have created a comprehensive machine-learning pipeline tailored to predict hospital readmissions. To succeed, you'll need a good understanding of R programming language, including data manipulation and visualization using tidyverse packages and some knowledge of machine learning concepts. No prior experience with Tidymodels is required, making it accessible to anyone interested in leveraging data science for healthcare analytics. Join us on this transformative journey and become equipped to make a meaningful impact on patient care outcomes through data-driven insights.

What will i learn?

  • In this course you will learn about
  • Machine Learning
  • Data Analysis
Requirements
Curriculum for this course
1 Lessons 2 hrs 54 mins
Tidymodels in R: Building tidy machine learning models
1 Lessons 02:54:00 Hours
  • Tidymodels in R: Building tidy machine learning models
    Preview 02:54:00
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Includes:
  • 2 hrs 54 mins On demand videos
  • 1 Lessons
  • Access on mobile and tv
  • Full lifetime access