Binary-Image-Classification-Dogs-vs-Cats-CNN-VGG-16

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The "Dogs vs. Cats" dataset is a popular benchmark for image classification tasks, particularly for learning Convolutional Neural Networks (CNNs). It involves training a model to distinguish between images of dogs and cats, often using a subset (7,500) of a larger dataset. The larger dataset contains 17,500 images (8,750 cats and 8,750 dogs)

computervision convolutional-neural-networks image-recognition keras-classification-models keras-neural-networks keras-tensorflow pandas python transfer-learning vgg16-model

Creat：2025-07-20T07:36:10

Update：2025-09-30T06:16:38

https://www.kaggle.com/competitions/dogs-vs-cats/overview

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