Hey everyone ,
I am new to Weights & Biases and still figuring out how to make the most of it for my AI projects. I have been running some computer vision experiments & I really such as the way W&B tracks runs metrics and artifacts but I know there is a lot more it can do.
I took a Generative AI Course where W&B was mentioned for experiment tracking but they did not share many hands on tips. That is why I want to know how you all organize your projects Do you follow a certain structure for naming or tagging runs How do you manage & log large datasets without making the workspace messy Also how do you make sure your experiments are reproducible while avoiding unnecessary clutter.
I want to hear about your real world workflows or any small tricks that have made a big difference for you when using W&B.
Thank you.