microsoft/AI-For-Beginners
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lessons/4-ComputerVision/07-ConvNets/lab/README.md
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| 1 | # Classification of Pets Faces |
| 2 | |
| 3 | Lab Assignment from [AI for Beginners Curriculum](https://github.com/microsoft/ai-for-beginners). |
| 4 | |
| 5 | ## Task |
| 6 | |
| 7 | 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. This can be successfully done using neural networks. |
| 8 | |
| 9 | You need to train a convolutional neural network to classify different breeds of cats and dogs using **Pet Faces** dataset. |
| 10 | |
| 11 | ## The Dataset |
| 12 | |
| 13 | We will use the **Pet Faces** dataset, derived from [Oxford-IIIT](https://www.robots.ox.ac.uk/~vgg/data/pets/) pets dataset. It contains 35 different breeds of dogs and cats. |
| 14 | |
| 15 |  |
| 16 | |
| 17 | To download the dataset, use this code snippet: |
| 18 | |
| 19 | ```python |
| 20 | !wget https://mslearntensorflowlp.blob.core.windows.net/data/petfaces.tar.gz |
| 21 | !tar xfz petfaces.tar.gz |
| 22 | !rm petfaces.tar.gz |
| 23 | ``` |
| 24 | |
| 25 | ## Stating Notebook |
| 26 | |
| 27 | Start the lab by opening [PetFaces.ipynb](PetFaces.ipynb) |
| 28 | |
| 29 | ## Takeaway |
| 30 | |
| 31 | You have solved a relatively complex problem of image classification from scratch! There were quite a lot of classes, and you were still able to get reasonable accuracy! It also makes sense to measure top-k accuracy, because it is easy to confuse some of the classes which are not clearly different even to human beings. |
| 32 | |