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+# Obesity Risk Prediction CNN Model
+
+This repository hosts a Convolutional Neural Network (CNN) model that predicts the risk of obesity in individuals with an impressive accuracy of 87.01%. Developed on Google Colab, this model harnesses the platform's powerful GPUs and collaborative environment.
+
+## Model Overview
+
+- *Objective*: Accurately predict obesity risk from input data.
+- *Accuracy*: Attained 87.01% on the test dataset.
+- *Dataset*: Sourced from a Kaggle competition via its API.
+- *Frameworks*: Built with TensorFlow/Keras.
+- *Training Environment*: Google Colab.
+
+## Features
+
+- *Input*: Accepts data with shape (22, 1), including normalization and dropout layers.
+- *Output*: Outputs the probability of obesity risk.
+- *Architecture*: Consists of 5 layers, featuring convolutional layers, dropout layers, batch normalization, and fully connected layers.
+- *Optimization*: Utilizes the Adam optimizer with a learning rate of 0.00005.
+
+## Results
+
+In a sample test of 10, the model correctly predicted 8 instances, indicating potential areas for improvement to enhance accuracy.
+
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+
+Your contributions and feedback are invaluable as we continue to refine this model. Feel free to clone and explore its capabilities!