Cats vs dogs classification using deep learning. Data augmentation and convolutional neural networks.

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use CNN / DNN to classify the label of the image (cat/dog); image argumentation / transfer learning -> 95% accuracy or above

Repository for a deep learning model that classifies images as either cats or dogs using deep learning techniques. The model is trained on a diverse dataset and achieves high accuracy in distinguishing between these two popular pet categories. Includes pre-processing scripts, model architecture, and evaluation metrics for seamless implementation

Neural Network for Cats vs Dogs Classification. Created in May 2020.

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Image classification of cats and dogs

End-to-end CNN pipeline using TensorFlow/Keras for image classification (dogs vs. cats). Includes data preprocessing, training, evaluation, and inference scripts.

In this notebook, I build a high-accuracy Cat vs. Dog classifier using InceptionV3 and transfer learning. After thorough EDA and robust tf.data preprocessing, the model achieves ~99% test accuracy with strong generalization and no overfitting.

🐱 Classify cat and dog images using a convolutional neural network in Python with TensorFlow, enhancing your machine learning skills and understanding of image recognition.