ModelOps
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments.
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments.
The level of sophistication and integration of design practices within an organization's processes and culture.
A visual exercise that helps product teams understand and prioritize features by organizing user stories into a cohesive narrative that aligns with user journeys and goals.
An analysis that assesses the practicality and potential success of a proposed project or system.
The practice of comparing performance metrics to industry bests or best practices from other companies.
The process of identifying, assessing, and mitigating potential threats that could impact the success of a digital product, including usability issues, technical failures, and user data security.
A structured framework for product design that stands for Comprehend the situation, Identify the customer, Report customer needs, Cut through prioritization, List solutions, Evaluate trade-offs, and Summarize recommendations.
Mutually Exclusive, Collectively Exhaustive (MECE) is a problem-solving framework ensuring that categories are mutually exclusive and collectively exhaustive, avoiding overlaps and gaps.
Average Revenue Per Account (ARPA) is a metric used to measure the average revenue generated per user or account.