Metropolis-Hastings Algorithm
Definition The Metropolis-Hastings Algorithm is a method used in AI and statistical computing to estimate the probability distribution of complex data when it’s difficult to assess directly. It’s based on Markov Chain Monte Carlo (MCMC) techniques to generate a sequence of samples from the probability distribution. This algorithm is especially useful in optimizing marketing strategies […]
Markov Decision Process (MDP)
Definition The Markov Decision Process (MDP) in marketing AI is a mathematical model used to make optimal decisions in situations where outcomes are partly random and partly under an entity’s control. It’s based on the Markov property, where the probability of transitioning to any particular state depends solely on the current state and the decision […]
Memory-Augmented Neural Networks
Definition Memory-Augmented Neural Networks (MANN) in marketing refers to an Artificial Intelligence (AI) model that utilizes an external memory component for storage and manipulation of data over long periods. This complements a traditional neural network’s ability to process and learn from raw data seamlessly. With MANN, marketers can save, access, and utilize historical data efficiently, […]
Multi-Armed Bandit
Definition In marketing, the term Multi-Armed Bandit refers to an AI-based algorithm used for efficient resource allocation in experimentation. It dynamically shifts traffic or resources to different options based on their performance to maximize overall returns. This approach provides a balance between exploring new tactics and exploiting proven strategies. Key takeaway The Multi-Armed Bandit is […]
Multi-layer Perceptron (MLP)
Definition A Multi-layer Perceptron (MLP) is a type of artificial neural network (ANN) model in AI, that is comprised of multiple layers of perceptron, simple artificial neurons. The layers include at least one hidden layer apart from input and output layers, which help to process complex data through weighted inputs and activation functions. In marketing, […]
Multitask Learning
Definition Multitask Learning in AI marketing refers to an approach where a single AI model is trained to perform multiple tasks simultaneously. The aim is to improve the model’s performance and efficiency by sharing information between tasks. This approach believes that tasks are related and the learning process will be more effective when they are […]
Manifold Learning
Definition Manifold Learning in AI refers to a set of unsupervised dimensionality reduction techniques. These methods work by creating a low-dimensional representation of high-dimensional data, while preserving key relationships or structures within the data. It’s often applied in marketing for customer segmentation, feature extraction, and data visualization by capturing complex, nonlinear similarities among data points. […]
Model-Based Reinforcement Learning
Definition Model-Based Reinforcement Learning (MBRL) in marketing is a type of artificial intelligence that uses predictive models to understand the environment and make strategic decisions. It involves training an agent to learn by taking actions that maximize reward based on its understanding of the model. This approach allows for more efficient learning, as the agent […]
Multi-Task Learning
Definition Multi-Task Learning (MTL) in AI marketing refers to a machine learning approach where a model is trained to perform a variety of related tasks simultaneously, with the aim of improving the model’s performance. The underlying principle is that the various tasks will share useful information, thereby improving the model’s overall efficiency and accuracy. In […]
Multi-Instance Learning
Definition Multi-Instance Learning (MIL) in AI marketing refers to a type of machine learning where data is grouped in bags or sets, with each bag labeled as positive if it contains at least one positive instance, and negative if it contains none. It’s often used in scenarios where labeling individual instances within a bag is […]
