The Cardiovascular Disease dataset is a collection of health-related information used for analyzing and predicting cardiovascular diseases. It encompasses diverse data such as age, gender, blood pressure, cholesterol levels, and lifestyle factors. This dataset serves as a valuable resource for researchers and healthcare professionals to better understand and mitigate the risks associated with cardiovascular diseases.
Make sure you have the following prerequisites installed:
- Python (version >= 3.6)
- Jupyter Notebook (optional, for exploring and running the notebooks)
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Clone the repository:
git clone https://github.com/DeveloperRedoy/ML-Cardiovascular.git
| Apply Algorithm List | Kaggle Link |
|---|---|
| Linear Regression | https://www.kaggle.com/code/mdredoysarder/cardiovascular/edit |
| Logistic Regression | |
| Decision Tree | |
| Random Forest | |
| AdaBoost (Adaptive Boosting) | |
| Gradient Boosting Machines (GBM) | |
| Support Vector Machines(SVM) | |
| K-Nearest Neighbors (KNN) | |
| Naive Bayes | |
| Principal Component Analysis (PCA) |
🏆 Machine learning project🏆
You can use this service for free. I'm looking for sponsors to help us keep up with this service❤️
| Social accounts | Link |
|---|---|
| https://twitter.com/FreelancerRedoy | |
| https://www.linkedin.com/in/redoytime/ | |
| https://www.facebook.com/redoy.sarder.714 | |
| Kaggle | https://www.kaggle.com/mdredoysarder |
| Profile | https://www.hackerrank.com/profile/syber_redoy_php |
| Github | https://github.com/Redoy365 |