MixMatch
Definition MixMatch in AI marketing refers to a self-supervised learning strategy for image classification. It uses both labeled and unlabeled data to train an AI system to accurately classify images. By incorporating diversity of image augmentation, it helps in improving the accuracy of prediction models in machine learning. Key takeaway MixMatch is an AI methodology […]
Mixup
Definition Mixup in AI marketing is a data augmentation technique used to create synthetic data. It involves taking a pair of inputs and combining them to produce a new input. The purpose is to make the AI model more robust by providing it with a wider range of data and reducing overfitting. Key takeaway Mixup […]
Machine Translation
Definition Machine Translation is an aspect of AI in marketing which refers to the use of automated software to translate text or speech from one language to another. This technology can effectively break down language barriers, allowing businesses to communicate with international audiences efficiently. Machine Translation uses algorithms to learn from repeated patterns in data, […]
Marketing Data Cleansing
Definition Marketing Data Cleansing in AI is a process that involves the use of technology to correct, remove, or consolidate inaccurate, duplicate, or improperly formatted data in a marketing database. This practice enhances the quality and accuracy of the data, making it more reliable for marketing campaigns and decision-making. It is critical step in a […]
Market Basket Analysis
Definition Market Basket Analysis is a data mining technique used in marketing to identify product purchasing patterns by analyzing customer buying habits. It leverages AI and machine learning algorithms to predict future purchase decisions based on past behaviors. The goal is to maximize sales by cross-selling, upselling, and promoting relevant products together. Key takeaway Market […]
Marketing Attribution Modeling
Definition Marketing Attribution Modeling in AI refers to the process of utilizing artificial intelligence techniques to evaluate and understand how different marketing channels and touchpoints contribute to a customer’s decision to make a purchase. It helps in assigning quantifiable value to each interaction along a customer’s journey, aiding marketers to make informed decisions about strategic […]
Meta-Reinforcement Transfer Learning
Definition Meta-Reinforcement Transfer Learning in marketing refers to AI systems’s ability to learn a variety of tasks and transfer knowledge from one task to another, enhancing overall performance. It is a subset of AI that incorporates aspects of both reinforcement learning and transfer learning. This approach fosters rapid learning with a fewer data points based […]
Meta-Hierarchical Transfer Learning
Definition Meta-Hierarchical Transfer Learning in AI marketing refers to an advanced approach in machine learning where knowledge gained while solving one problem (usually involving hierarchical data structures) is applied to different but related problems. This technique promotes efficiency as it reduces computational requirements through the reuse of the said knowledge. In marketing, it can enhance […]
Meta-Progressive Transfer Learning
Definition Meta-Progressive Transfer Learning in AI marketing refers to a methodology where a machine learning model utilizes knowledge gained from processing one task to enhance performance on a subsequent, related task. It’s termed ‘meta-progressive’ because this learning process continues to grow and progress as more tasks are learned and the model makes connections between them. […]
Meta-Incremental Transfer Learning
Definition Meta-Incremental Transfer Learning in AI marketing refers to a machine learning strategy that leverages previously acquired knowledge from one task to improve the learning efficiency or performance on a subsequent, but related task. It incorporates the ‘incremental’ principle, meaning the AI progressively learns over time, handling newer tasks while retaining the knowledge from earlier […]
