How to decide which neural network to use wider or deeper?

Question

Accepted Answer

The decision between wider or deeper neural networks depends on the complexity of the data and the trade-off between computational resources and performance.

Consider the complexity of the data: Deeper networks are better for more complex data, while wider networks are better for simpler data.
Evaluate computational resources: Deeper networks require more computational resources and training time compared to wider networks.
Experiment with both architectures: Try training models with different widths and depths to see which performs better on your specific task.
Use transfer learning: Pre-trained models can provide a good starting point and help in deciding between wider or deeper networks.
Consider regularization techniques: Regularization methods like dropout can help prevent overfitting in deeper networks.

How to decide which neural network to use wider or deeper?

Popular interview questions of ml engineer