AI Workflow Glossary: Your Go-To Guide for Workflow and Automation Terms
Experimentation
Experimentation in the context of data science and machine learning refers to the process of testing.
Fairness Evaluation
Fairness evaluation in machine learning and artificial intelligence refers to the process of assessing and ensuring that a model's predictions.
Feature Engineering
Feature Engineering is the process of using domain knowledge to select, modify, or create new features (attributes) from raw data.
Feature Scaling
Feature scaling is the process of standardizing or normalizing the range of independent variables or features in a dataset.
Feature Selection
Feature Selection is the process of selecting a subset of relevant features (attributes) from a larger set of features for use in building machine learning models.
Fiber Project Workflow Automation
Fiber Project Workflow Automation refers to the use of automation tools and processes specifically designed to manage and streamline workflows related to fiber optic projects.
Field Update
A Field Update is an automated action in a business process or system that changes the value of a specific field.
Field Workflow Automation
Field Workflow Automation refers to the use of technology and automation tools to streamline and optimize workflows for field operations
Flexible Workflow Automation
Flexible Workflow Automation refers to the ability to create and manage workflows that can easily adapt to changing business needs, processes, or conditions.
Flow
Flow refers to the sequence or movement of tasks, data, or processes within a system, business operation, or workflow.
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