Evaluate the impact of an AI application used in the real world. (case study) : Working with Flower Images: Case Study -

The video tutorial discusses overfitting in deep learning models, explaining why it's important to test if a model can overfit on training data. It covers the process of overfitting using Resnet 18, observing loss reduction and accuracy improvements. The tutorial also addresses common issues like activation functions, learning rates, and optimizers, providing troubleshooting tips. Advanced solutions such as changing initialization techniques and network architecture are explored for persistent problems.

Discuss the importance of the learning rate in the training process.

What steps can be taken if a model is consistently outputting NaN values during training?

Why might changing the network architecture be necessary for improving model performance?