Join us for our next episode of Neterium Talks on November 23rd, where we'll be delving into the fascinating topic of Model Validation with Pascal Aerens, CPO at Neterium and Maxime Westphal, Full Stack Developer at Neterium.
To measure the performance and quality of the model in the light of our users' risk policies, Neterium has also developed a unique Model Validation tool. It relies on "predictive accuracy" to measure how close the model's predictions will be to what happens. A simple user interface allows uploading a data file, then provides a visual overview and comparison of multiple runs with different configurations and allows review of all test cases and scenarios in detail, highlighting conflicting or inconsistent expectations to suggest a new configuration for another run.
As always, we'll start with a quick overview of key updates in the space by Christopher Stringham, followed by a deep dive into a specific subject. The session will end with an open Q&A, where we can exchange ideas and discuss your thoughts.
The information provided has been researched and written with due diligence to offer insights and perspectives on the subject matter. However, it is important to note that this content is for informational purposes only and should not be construed as legal, regulatory, financial, or professional advice of any kind. Readers are urged to consult with qualified experts, advisors, or professionals relevant to their specific circumstances and needs before making any business, legal, or financial decisions. The content presented here may not be comprehensive or up-to-date, and the laws, regulations, and business environments can change rapidly. The authors, contributors, and our organization do not assume any liability for errors, omissions, or inaccuracies in the content, or for any actions taken based on the information provided in this thought leadership piece. Reliance on this content is solely at the reader's discretion. By accessing and reading this content, you agree to hold our organization and its authors harmless from any claims, losses, liabilities, or damages arising from the use or reliance on the information contained herein.
