This is an image classification in-class competition. The task is to use images of 10 different animals and train a model to classify them correctly. The details about the data is in the data tab. 

You are to download the data, which is made of two parts: train, which has both data and the label, and test, which only has data and not the label. You will train a model, and then predict the labels of the test dataset, and submit that result here in Kaggle. 

The accuracy score of your result will be shown in the leaderboard. The public leader board is scored on 50% of the test data, and the private leader board is scored on the other 50%. During the competition, you can submit results up to 20 times a day and see your result on public leaderboard. And when the competition is over, the final score will be shown in the private leaderboard. The two leaderboards, is to avoid people overfitting to the public leaderboard. 

You are free to use any programming languages, packages, and machine learning models. 

The grading of this part of the homework will be mostly based on the private leaderboard accuracy and ranking (40pts), and partially on the report (20pts).