🐶 End-to-end Multi-class Dog Breed Classification

This notebook builds an end-to-end multi-class image classifier using TensorFlow 2.x and TensorFlow Hub.

1. Problem

Identifying the breed of a dog given an image of a dog.

When I'm sitting at the cafe and I take a photo of a dog, I want to know what breed of dog it is.

2. Data

The data we're using is from Kaggle's dog breed identification competition.

https://www.kaggle.com/c/dog-breed-identification/data

3. Evaluation

The evaluation is a file with prediction probabilities for each dog breed of each test image.

https://www.kaggle.com/c/dog-breed-identification/overview/evaluation

4. Features

Some information about the data:

We're dealing with images (unstructured data) so it's probably best we use deep learning/transfer learning. / There are 120 breeds of dogs (this means there are 120 different classes).

There are around 10,000+ images in the training set (these images have labels). There are around 10,000+ images in the test set (these images have no labels, because we'll want to predict them).

• Get our workspace ready
• Import TensorFlow 2.x ✅
• Import TensorFlow Hub ✅
• Make sure we're using a GPU ✅

Note: Project done in course: Complete Machine Learning & Data Science Bootcamp 2023 by Zero to Mastery