CIFAR_10-Dataset-Classifier

• CIFAR-10 is a dataset that consists of several images divided into the following 10 classes: 0. Airplanes

  1. Cars
  2. Birds
  3. Cats
  4. Deer
  5. Dogs
  6. Frogs
  7. Horses
  8. Ships
  9. Trucks

• The dataset stands for the Canadian Institute For Advanced Research (CIFAR)

• CIFAR-10 is widely used for machine learning and computer vision applications.

• The dataset consists of 60,000 32x32 color images and 6,000 images of each class.

• Images have low resolution (32x32).

• In this notebook uses two models

• frist one is CNN model with

  • training accuracy: 87.7%
  • test accuracy: 77.3%

• second model is Upsampling layer ==> ResNet-50 ==> two Dense layers then one last Dense layer for output

  • training accuracy: 97.8%
  • test accuracy: 88.4%

• each model runed for 10 epochs without data augmentation

Source: Rayan Ahmed - Machine Learning Practical Workout - 8 Real-World Projects