Tidymodels in R: Building tidy ml models
Develop a machine learning pipeline that utilizes Tidymodels to forecast hospital readmissions, with potential applications in healthcare analytics.
Description for Tidymodels in R: Building tidy ml models
Features of the Course:
Data Preprocessing and Visualization: Using Tidymodels, import, investigate, and prepare clinical data for machine learning through data splitting, data visualizations, and summary tables.
Development of Predictive Models: Utilize hands-on practice to develop and optimize classification models with Tidymodels for practical applications.
Model Evaluation and Selection: Select the most effective predictive model for reducing hospital readmissions by assessing model performance using pertinent metrics and techniques.
Healthcare Analytics: A Practical Approach: Develop a machine learning pipeline that is designed to enhance patient care outcomes by working within a real-world healthcare scenario.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 21
Offered by: On Coursera provided by Coursera Project Network
Duration: 2 hours at your own pace
Schedule: Hands-on learning
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