Update README.md

README.md

@@ -6,4 +6,41 @@ metrics:
 tags:
 - health
 - classification
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+---
+
+# Model Name
+
+## Overview
+This repository contains the implementation of a machine learning model for predicting [mention the task or purpose of the model]. The model is trained using [describe the dataset used for training].
+
+## Dataset
+The dataset used for training this model is sourced from [https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease/data]. It consists of [319795] instances and [18] features. The dataset was preprocessed using various techniques, including:
+- Handling missing values
+- Encoding categorical variables
+- Feature scaling or normalization
+
+## Model Architecture
+The model architecture includes the following algorithms:
+- Logistic Regression
+- K-Nearest Neighbors (KNN)
+- Naive Bayes
+- Decision Tree
+- Random Forest
+- Long Short-Term Memory (LSTM)
+- Convolutional Neural Network (CNN)
+
+## Cleaning Techniques
+During preprocessing, the following cleaning techniques were applied to the dataset:
+- Encoding categorical variables: Categorical variables were encoded using one-hot encoding.
+- Feature scaling or normalization: Numerical features were scaled or normalized to ensure uniformity across different features.
+
+
+
+## Usage
+To use the model, clone this repository and follow the instructions provided in the respective model's directory. Each algorithm has its implementation and usage instructions.
+
+## License
+[Specify the license under which the model and code are released, e.g., MIT License, Apache License 2.0, etc.]
+
+## Contact
+For questions or inquiries, please contact [your email or contact information].