Binary Cat vs Dog Classifier

A binary image classifier using deep learning to distinguish between cats and dogs. Built with TensorFlow and Keras, featuring convolutional neural network architecture, data augmentation pipelines, and comprehensive model performance evaluation.

Features

• Binary classification — distinguish between cat and dog images
• CNN architecture — multi-layer convolutional neural network for feature extraction
• Data augmentation — image transformations for improved model generalization
• Training pipeline — complete training loop with validation and checkpointing
• Performance evaluation — accuracy, loss curves, and confusion matrix analysis
• Jupyter Notebook — fully documented, step-by-step implementation

Tech Stack

• Python 3 — Core programming language
• TensorFlow / Keras — Deep learning framework
• Jupyter Notebook — Interactive development environment
• NumPy / Matplotlib — Data processing and visualization

Getting Started

git clone https://github.com/giovanniromero-dev/binary-cat-dog-classifier.git
cd binary-cat-dog-classifier
# Open the notebook in Jupyter or Google Colab
jupyter notebook binary-cat-dog-classifier.ipynb

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Built with dedication by Giovanni Romero