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This project uses deep learning and transfer learning with TensorFlow to classify dog breeds from images. Trained on the top 10 breeds from the Kaggle dataset, the model achieves over 94% validation accuracy.

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Dog-Breed-Prediction-based-on-Multi-class-Classification

A machine learning model leveraging the benefits of transfer learning to recognize the breed of a dog from an uploaded image.

This model uses images from the Kaggle Dog Breed Identification dataset to train itself on the 10 most frequent breeds.

Steps Involved in Making the Model:

  1. Downloading the Data and Setting Up the Environment:

  2. Preprocessing the Data:

  3. Building the Model:

  4. Training the Model:

  5. Evaluating the Model:

Test Results After training and testing, the following accuracy was achieved:

94.3% was achieved using the MobileNetV2 Transfer Learning model.

About

This project uses deep learning and transfer learning with TensorFlow to classify dog breeds from images. Trained on the top 10 breeds from the Kaggle dataset, the model achieves over 94% validation accuracy.

Topics

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1 star

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0 watching

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