using cnn and mlp to classify cidfar10 In this code, multi-layer perceptron or so called (mlp) and convolutional neural network or so called (cnn) will be used to solve the classification problem of cifar10 dataset of images of different objects and animals. Data augmentation is used to make classification independent of rotation and scale of the image.
- matplotlib
- pandas
- numpy
- keras
Clone the repository and navigate to the downloaded folder and run the following commands
python3 cifar10_augmentation.py
or
python3 cifar10_cnn.py
or
python3 cifar10_mlp.py
(Optional) If you plan to install TensorFlow with GPU support on your local machine, follow the guide to install the necessary NVIDIA software on your system. If you are using an EC2 GPU instance, you can skip this step.