Best Practice: Deep Learning Checklist

This Deep Learning Checklist covers a wide array of critical topics, from the foundational steps of organizing code repositories and managing datasets to the nuanced tasks of model evaluation and augmentation. It serves as a structured roadmap, ensuring that all essential aspects of a deep learning project are addressed, thereby maximizing the chances of its success. By adhering to this checklist, developers can avoid common pitfalls, streamline their workflows, and achieve better results in a shorter timeframe.