Deepchecks x W&B
Test & Validate Your ML Models and Data
What to expect?
With real-life data being dynamic and noisy, and with the black-box nature of machine learning models, comprehensive validation of ML-based systems is challenging. Do you want to decrease the chances that you’ll be surprised by faulty data or weird model predictions? Join the webinar to learn about: - Types of problems that ML models face (i.e. data integrity and distributions, ML methodology pitfalls, model evaluation related issues) - Best practices for validation: when, how and what to test for In addition, we’ll present a live demo of using the deepchecks open source package for effective validation with minimal effort, and present the recent option to integrate the validation’s results with W&B.