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+# Classification of Oxford Pets using Transfer Learning
+
+Lab Assignment from [AI for Beginners Curriculum](https://github.com/microsoft/ai-for-beginners).
+
+## Task
+
+Imagine you need to develop and application for pet nursery to catalog all pets. One of the great features of such an application would be automatically discovering the breed from a photograph. In this assignment, we will use transfer learning to classify real-life pet images from [Oxford-IIIT](https://www.robots.ox.ac.uk/~vgg/data/pets/) pets dataset.
+
+## The Dataset
+
+We will use the original [Oxford-IIIT](https://www.robots.ox.ac.uk/~vgg/data/pets/) pets dataset, which contains 35 different breeds of dogs and cats.
+
+To download the dataset, use this code snippet:
+
+```python
+!wget https://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz
+!tar xfz images.tar.gz
+!rm images.tar.gz
+```
+
+## Stating Notebook
+
+Start the lab by opening [OxfordPets.ipynb](OxfordPets.ipynb)
+
+## Takeaway
+
+Transfer learning and pre-trained networks allow us to solve real-world image classification problems relatively easily. However, pre-trained networks work well on images of similar kind, and if we start classifying very different images (eg. medical images), we are likely to get much worse results.