In this project, you’ll help a leading healthcare organization build a model to predict the likelihood of a patient suffering a stroke. The model could help improve a patient’s outcomes. Working with a real-world dataset, you’ll use R to load, clean, process, and analyze the data and then train multiple classification models to determine the best one for making accurate predictions.


Build and deploy a stroke prediction model using R
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目标
Explore the dataset to identify the most important patient and/or clinical characteristics
Build a well-validated stroke prediction model for clinical use
Deploy the model to enhance the organization's clinical decision-making
您将展示的技能
- Feature Engineering
- Application Deployment
- Data Cleansing
- R Programming
- Data Analysis
- Statistical Modeling
- Interactive Data Visualization
- Classification And Regression Tree (CART)
- Machine Learning Methods
- Applied Machine Learning
- Machine Learning
- Data Transformation
- Data Manipulation
- Predictive Modeling
- Exploratory Data Analysis
- Statistical Analysis
要了解的详细信息
可分享的工作示例
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授课语言:英语(English)
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关于此项目
项目规划
此项目要求您独立完成以下步骤:
Import data and data preprocessing
Build prediction models
Evaluate and select prediction models
Deploy the prediction model


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