What are some effective debugging tools for AI development?

What are some effective debugging tools for AI development?

There are several effective debugging tools for AI development, such as TensorBoard, PyTorch Debugger, and Weights & Biases. These tools help visualize model training, track experiments, and debug code.

Can you explain how TensorBoard works?

TensorBoard is a visualization toolkit for TensorFlow that allows you to visualize metrics like loss and accuracy over time, view model graphs, and analyze histograms of weights and biases.

Are there any tools specifically for debugging neural networks?

Yes, tools like Netron and Deep Learning Studio are specifically designed for visualizing and debugging neural networks, helping you understand the architecture and flow of data.

How do I choose the right debugging tool for my project?

Choosing the right debugging tool depends on your specific needs, such as the framework you're using, the complexity of your model, and whether you need visualization or just logging capabilities.