Indian Buffet Process
Definition The Indian Buffet Process (IBP) is a statistical method used in artificial intelligence (AI) and machine learning, not a marketing term. It’s a Bayesian nonparametric model that allows for an infinite number of features in the data. The name “Indian Buffet Process” comes from a metaphor which compares features to dishes in a buffet, […]
Incremental Transfer Learning
Definition Incremental Transfer Learning in AI pertains to the process of leveraging a pre-trained model on a new related task, then continually updating the model with knowledge from each new task it learns, hence, incrementally improving its performance. This method promotes efficiency as the model doesn’t need to learn from scratch each time, instead, it […]
Instance-Based Transfer Learning
Definition Instance-Based Transfer Learning is a type of Artificial Intelligence approach in marketing where data or knowledge from previously solved problems is used to solve new, similar issues. It employs the understanding from specific instances in one domain to enhance the learning process in another related domain. It’s often used to improve predictive accuracy and […]
Instance-Level Transfer Learning
Definition Instance-Level Transfer Learning in marketing AI refers to the application of machine learning models which leverage past data or knowledge obtained from one context to a new, but similar context. Specifically, it tailors the AI models to individual instances or customers based on their unique characteristics or behavior. This approach enables marketers to customize […]
Instance Transfer Learning
Definition Instance Transfer Learning in AI marketing is a technique where the model leverages knowledge from previously learned tasks to improve the learning performance in a new but related task. Essentially, it’s a way for machine learning models to apply what they’ve learned in one context to another, different context. This can result in more […]
Inductive Transfer Learning
Definition Inductive Transfer Learning in AI refers to a machine learning approach where knowledge gained while solving one problem is applied to a different but related problem. It’s often used in marketing to improve the efficiency and accuracy of AI systems, enabling them to recognize and apply patterns or insights across different yet connected marketing […]
In-Domain Transfer
Definition In-Domain Transfer in marketing refers to the process of applying machine learning models that were trained on a particular task (domain) to a similar or related task within the same domain. It leverages the knowledge gained from the initial training to accelerate or improve the learning performance in the new task. Therefore, it helps […]
Image Recognition
Definition Image Recognition in AI marketing refers to the technology that identifies objects, places, people, or actions in images using artificial intelligence. It allows machines to visually sense the world, similarly to how humans use their sight. This technology commonly finds use in applications such as data analysis, user interface optimization, and targeted advertising. Key […]
Image Segmentation
Definition AI in Image Segmentation refers to the use of artificial intelligence in dividing digital images into multiple parts or segments for easier analysis or understanding. It involves the process of assigning labels to every pixel in the image such that pixels with the same label share certain characteristics. In marketing, it helps in object […]
Image Registration
Definition Image Registration in AI marketing refers to the process of aligning different sets of data into one coordinate system. This method is extensively used in AI to match multiple images of the same scene, which contributes to the tracking of movement over time or combines information from different viewpoints. It helps businesses provide a […]
