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1 | 1 | Description: |
2 | 2 | The project uses TensorFlow and Keras libraries to create a Convolutional Neural Network (CNN) architecture for Cats vs. Dogs image classification. The dataset is preprocessed by resizing and normalizing the images. The CNN model consists of multiple convolutional and pooling layers, followed by fully connected layers for classification. The model is trained using the training data, optimizing the cross-entropy loss with the Adam optimizer |
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4 | | -Dataset: |
5 | | -https://drive.google.com/file/d/12I9KXycZQb3OFnb4UySFc8iHscdCZ0yJ/view?usp=sharing |
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7 | 4 | Model Summary: |
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8 | 6 |  |
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10 | 8 | Output: |
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11 | 10 |  |
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| 13 | +Dataset: |
| 14 | +https://drive.google.com/file/d/12I9KXycZQb3OFnb4UySFc8iHscdCZ0yJ/view?usp=sharing |
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