Validation Set: A subset of data used to assess the performance of an AI model during training, helping to tune hyperparameters and prevent overfitting.
Variance: Variance in AI refers to the model’s sensitivity to variations in the training data, with high variance indicating that the model is overly responsive to noise.
Vector Space Model: A mathematical representation used in natural language processing (NLP) to convert text documents into numerical vectors for analysis and similarity calculations.
Version Control: A system that tracks and manages changes to code, models, or data, allowing collaborative development and preserving historical versions.
Virtual Reality (VR): A technology that immerses users in a computer-generated environment, often used for simulations, training, and immersive experiences.
Viterbi Algorithm: A dynamic programming technique used in AI for finding the most likely sequence of hidden states in a hidden Markov model, commonly applied in speech recognition and error correction.
Vocabulary: In natural language processing (NLP), vocabulary refers to the set of unique words or terms in a text corpus, used for tasks like text analysis and language modeling.
Voice Recognition: An AI technology that converts spoken language into text or commands, enabling hands-free control of devices and applications.
