Double deep Q-learning reduces overestimated action values in deep Q-learning by splitting the max operation in the target into separate action selection and action evaluation steps, resulting in more stable and accurate learning.
From regular check-ins to product adoption scores, these are the metrics seven customer success professionals have found the most effective for engaging customers — and mitigating churn.
