Project Summary:
- Achieved an accuracy of 90% in classifying the images at hand of the famous CIFAR-10 dataset using Convolutional Neural Networks (CNN).
- Normalized and Pre-processed the images and output label were one hot encoded, for better accuracy.
- Randomization and Dropout mechanisms were employed and tuned effectively, which increased accuracy from 90% to 92%