A tutorial on how to build a cancer detection model all while tracking of your experiments, storing model weights, optimizing hyperparameters, and more in W&B

As part of this report, I am going to show you how to use MS Excel (and maybe a better way too) to track all your experiments.

As part of this report, I am going to show you how to save model weights locally after every epoch during model training. As part of this report we will also look at a more scalable way of storing model weights.

As part of this report I showcase how to prepare the dataset for the ISIC Melanoma competition and upload it as a W&B artifact.