# Hackathon 2022

## EESTEC - Electrical Engineering STudents’ European assoCiation

### Dataset: subset of CIFAR-10 dataset
The dataset consists of 40.000 images for training divided into 8 categories. The test batch contains exactly 1000 randomly-selected images from each class. 

Here are the classes in the dataset:
- airplane
- automobile
- bird 
- cat
- dog
- horse
- ship
- truck

The classes are completely mutually exclusive. There is no overlap between automobiles and trucks. "Automobile" includes sedans, SUVs, things of that sort. "Truck" includes only big trucks. Neither includes pickup trucks.

Reference to the initial dataset: [The CIFAR-10 dataset](https://www.cs.toronto.edu/~kriz/cifar.html).



Within this task, you are advised to use python. Python packages that may be useful are: _NumPy, Scikit−learn, Matplotlib, Pandas, TensorFlow, PyTorch_.

## Programming:
- For the programming part, you can turn to StackOverflow if you bump into some kind of bug or problem, but again we strongly advise against copying code for these simple tasks.
- Implement your approach using a Jupyter Notebook, with sufficient but not redundant comments.