Prescriptive Analytics
The use of data, algorithms, and machine learning to recommend actions that can achieve desired outcomes. Essential for optimizing decision-making and implementing effective strategies.
The use of data, algorithms, and machine learning to recommend actions that can achieve desired outcomes. Essential for optimizing decision-making and implementing effective strategies.
A recommendation system technique that suggests items similar to those a user has shown interest in, based on item features. Important for providing personalized recommendations and improving user satisfaction.
A system that suggests products, services, or content to users based on their preferences and behavior. Essential for personalizing user experiences and increasing engagement and conversion rates.
A recommendation system technique that makes predictions about user interests based on preferences from many users. Essential for personalizing user experiences and improving recommendation accuracy.
An interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Essential for driving data-informed decision making, predicting trends, and uncovering valuable insights in digital product design and development.
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance. Fundamental for developing and evaluating machine learning models in digital product design.
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
The practice of selling additional products or services to an existing customer. Essential for increasing revenue and enhancing customer value.
The process of tailoring a product or experience to meet the individual needs and preferences of users. Essential for enhancing user engagement and satisfaction by delivering relevant experiences.
AI systems that can dynamically adjust their behavior based on new data or changes in the environment. Important for developing systems that can respond to real-time changes and improve over time.