Transformer Models

Definition Transformer Models in AI marketing refer to a deep learning model primarily used in the field of natural language processing. They use attention mechanisms to significantly improve the understanding of contextual relationships between words in a text. These models are particularly effective at producing high-quality, personalized marketing content and interpreting customer data. Key takeaway […]

t-Distributed Stochastic Neighbor Embedding (t-SNE)

Definition t-Distributed Stochastic Neighbor Embedding (t-SNE) in AI marketing is a machine learning algorithm used for visualizing high-dimensional data by giving each data point a location in a two or three-dimensional map. It works by computing the probability that pairs of data points in the high-dimensional original space are related, then choosing a low-dimensional representation […]

Thompson Sampling

Definition Thompson Sampling is an algorithm used in AI marketing to balance exploration and exploitation when choosing advertisements to display. The algorithm estimates the probability of success for each advertisement option and randomizes selection based on these probabilities. This method allows ongoing learning from each new interaction, optimizing the ad choices over time. Key takeaway […]

Transcribing Services

Definition AI in Transcribing Services refers to the use of artificial intelligence technologies to convert spoken language into written text. This process is automated and can be much faster and more accurate than manual transcription. AI Transcribing Services are often used in marketing to transcribe interviews, meetings, webinars, or promotional videos. Key takeaway Transcribing Services […]

Text Generation Models

Definition Text Generation Models in AI marketing refer to machine learning-based algorithms that can automatically generate written content. These AI models analyze language patterns, context, and structure in existing text data, then produce new text that mirrors the style, tone or content of the analyzed data. They’re often used in marketing to generate product descriptions, […]

Text Classification

Definition Text Classification in AI marketing refers to the process of assigning predefined categories or labels to textual content. It’s based on the content’s contextual meaning and is powered by machine learning algorithms. This method is helpful in organizing, structuring, and understanding the massive amounts of text data in marketing, such as customer emails, product […]

Tokenization

Definition Tokenization in AI marketing refers to the process of converting sensitive data into unique identification symbols, or “tokens,” that retain necessary information without compromising security. These tokens can then be used in various marketing operations without exposing the actual data. This aids in data protection and privacy while enabling deep and secure data analytics. […]

Transductive Transfer Learning

Definition Transductive Transfer Learning in AI marketing refers to the application of machine learning models developed for one task to a related but distinct task, leveraging shared patterns or features without the need for explicit retraining. It essentially ‘transfers’ knowledge from one context to another. This is usually done to improve the performance and accuracy […]

Transferable Features

Definition Transferable Features in AI marketing refer to learned characteristics or knowledge by an AI system that can be applied or shifted from one campaign or context to another. These features enable the AI to adapt its algorithm based on previous experiences to enhance future marketing efforts. This concept allows for more precise targeting and […]

Transfer Learning

Definition Transfer Learning in AI marketing is a technique where a pre-trained model is adapted for a different but related problem. Instead of learning from scratch, it leverages knowledge from one context to a different one, reducing the time and computational resources required. It allows models to improve and streamline work processes by applying learned […]