Classifying images of everyday objects using a neural network
1 min readJun 13, 2020
The ability to try many different neural network architectures to address a problem is what makes deep learning really powerful, especially compared to shallow learning techniques like linear regression, logistic regression etc.
In this assignment, you will:
- Explore the CIFAR10 dataset: https://www.cs.toronto.edu/~kriz/cifar.html
- Set up a training pipeline to train a neural network on a GPU
- Experiment with different network architectures & hyperparameters
As you go through this notebook, you will find a ??? in certain places. Your job is to replace the ??? with appropriate code or values, to ensure that the notebook runs properly end-to-end. Try to experiment with different network structures and hypeparameters to get the lowest loss.
You might find these notebooks useful for reference, as you work through this notebook:
