Create README.md

README.md

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+---
+license: mit
+metrics:
+- accuracy
+library_name: keras
+---
+
+# Malaria Detection - Custom CNN Model
+
+## Model Description
+
+This is a custom Convolutional Neural Network (CNN) trained to detect malaria parasites in cell images. The model classifies blood cell images as either **Parasitized** or **Uninfected**.
+
+## Model Architecture
+
+- 3 Convolutional layers with ReLU activation
+- MaxPooling layers for downsampling
+- Dropout layer (0.5) for regularization
+- Dense layers for classification
+- Binary output with sigmoid activation
+
+## Training Details
+
+- **Dataset**: Cell Images for Detecting Malaria
+- **Input Size**: 150x150x3
+- **Optimizer**: Adam
+- **Loss Function**: Binary Crossentropy
+- **Epochs**: 10
+- **Validation Split**: 20%
+
+## Performance
+
+- **Validation Accuracy**: {history.history['val_accuracy'][-1]:.4f}
+- **Validation Loss**: {history.history['val_loss'][-1]:.4f}