Dog Bread Classification

Introduction

In this notebook, I will use a pretrained model to classify dog breeds. I will use the ResNet50 model, which is a deep learning model that has already been trained on a large dataset. I will use the model to classify dog breeds from images of dogs. The model is trained on the ImageNet dataset, which has 1000 classes of objects. I will use the model to classify dog breeds from the 120 classes of dog breeds in the Stanford Dogs dataset.

Data

The data is from the Stanford Dogs dataset, which contains 20,580 images of 120 breeds of dogs. The dataset is divided into 12,000 images for training, 8580 images for testing, and 8580 images for validation. The images are in JPEG format and have varying dimensions.

Approach

I will use the ResNet50 model to classify the dog breeds. I will use the model to predict the breed of the dogs in the test set and then evaluate the performance of the model using the accuracy metric.

Outline

1. Import Libraries
2. Load and Preprocess Data
3. Load Pretrained Model
4. Train Model
5. Evaluate Model
6. Conclusion