We have recently encountered an unusual method 👀 for delivering feedback.
While we appreciate the help with the QA, we believe that open source communities should be about value for the users and not an arena for battles between competitors.
This package is built and maintained by Deepchecks, an MLOps startup company. We're a team of data scientists and software engineers that recognize the rising influence of machine learning models on our day-to-day life, and want to make sure these models are working as they are expected to.
We've built and released this package to help ML practitioners test and validate their models and catch issues in their models as early as possible, so all of us can keep enjoying the benefits of ML algorithms.
We believe that open source is the natural and healthy way into the hearts of ML practitioners. It is also a healthy way to learn about their preferences and benefit from their contributions and suggestions. We will welcome any worthy contribution or comment, even if it comes from our competitors, since we believe our users should come first.
Our preferred way for feedback is: