End-to-End Dog Vision Multi-Class Dog Breed Classification

This notebook builds a end-to-end multi class image classifier using Tensorflow 2 and Tensorflow Hub

1. Problem:
Identifying the breed of a dog given an image of a dog.

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. Feautures:

Some information about the data:

* 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).

Getting our data ready (turning into Tesnors). Access the data and turn into ternsors using TensowFlor libary.

Accessing our data and checking out the label:

df = pd.read_csv(“data/heart-disease.csv”)