What is Multimodal Model? An AI model trained to handle multiple modalities of data, such as text, images, and audio. This allows the model to understand and leverage information from various sources for better decision-making.
What is N-Shot Learning? A machine learning technique where the model is trained on a very limited number of examples per class (N shots). This is particularly useful for situations where labeled data is scarce.
What is Natural Language Interface (NLI)? A system that allows users to interact with computers or applications using natural language, such as spoken language or text messages. NLIs bridge the gap between human language and machine understanding, enabling users to interact with technology in a more natural way.
What is Natural Language Processing (NLP)? A subfield of AI that deals with the interaction between computers and human language, enabling machines to understand and respond to human language.
Natural Language Processing (NLP)? Natural Language Processing (NLP) refers to the application of AI to understand, interpret, and generate human language. NLP is a multidisciplinary field that blends aspects of artificial intelligence (AI), computational linguistics, and computer science. It paves the way for machines to understand, interpret, and respond to human language in meaningful way-bridging […]
What is a Neural Network? A computational model inspired by the structure and function of the human brain. It consists of interconnected nodes (artificial neurons) that process information and learn through training. Deep Learning models are a type of neural network architecture.
What is Normalization? The process of scaling data features to a common range or scale. Normalization can improve the performance of machine learning algorithms by ensuring all features contribute equally during training.
What is Ontology? A formal specification of a knowledge domain, defining the entities, relationships, and constraints within that domain.
What is Optimization? The process of adjusting the parameters of a machine learning model to achieve the best possible performance on a specific task. This typically involves minimizing a loss function that measures the difference between the model’s predictions and the desired outcomes.
What is Overfitting? A phenomenon where a machine learning model performs well on training data but fails to generalize effectively to unseen data. This often occurs when the model becomes too specific to the training data and loses its ability to learn broader patterns.