A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
For questions about the use/aspects/implementation/intuition/mathematical proofs of various Linear Algebra methods used in Machine Learning and AI algorithms.
For questions about the legal aspects and ramifications due to the creation/use of AI in various fields and applications (also laws in place to regulate the proper use of AI technology).
For questions about the use of Markov models in the field of AI/ML.
For questions related to Google in the context of AI (e.g. related to Google Translate). Google is an American multinational technology company specializing in internet-related services and products.
An interdisciplinary field concerned with the statistical or rule-based modeling of natural language from a computational perspective.
For questions about the concept of intelligence, not restricted to Artificial Intelligence, but applied also to intelligence in nature, quantification of intelligence (problem solving strength), and q…
For questions about implementation of Machine Learning and Artificial Intelligence algorithms in the Java programming language.
For questions related to explainable artificial intelligence (XAI), also known as interpretable AI, which refers to AI techniques that can be trusted and easily understood by humans, which are particu…
For questions related to the mathematical concept of "expectation" or "expected value".
For questions related to the Bellman equations in the context of reinforcement learning (and other artificial intelligence subfields).
For questions related to speech recognition, also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT), which is a sub-field of computational linguistics th…
For questions related to the concept of learning rate (of an optimization algorithm, such as gradient descent) in machine learning.
For questions related to the Python's package scikit-learn (or sklearn).
For questions related to the exploration-exploitation trade-off (or dilemma) in the context of reinforcement learning.
For questions related to anomaly detection (or outlier detection) algorithms, which is the identification of rare items, events or observations which raise suspicions by differing significantly from t…
For questions related to pre-trained model. A pre-trained model is a model that was trained on a large benchmark dataset to solve a problem similar to the one that we want to solve. Accordingly, due …
For questions related to Thomas Bayes, his work and extension of his work, theory and applications.
For questions about meaning. Distinct from syntactics.
the study of graphs, which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of vertices, nodes, or points which are conn…
Refers to kinds of data with a high level of organization.
For questions about how quantum computing can advance the development of AI. Note that general questions about quantum computing are off-topic.
For questions related to the U-net, a neural network proposed in "U-Net: Convolutional Networks for Biomedical Image Segmentation" (2015) by Olaf Ronneberger et al. for semantic segmentation.
For questions related to the concept of generalization in computational learning theory and machine learning.
For questions about the application of Artificially Intelligent agents and Machine Learning Algorithms in the healthcare industry.
For questions related to incremental learning algorithms, which are algorithms that attempt to learn new information without forgetting all the previously learned one. Incremental learning is often a …
For questions related to "state of the art" (SOTA) models in machine learning and, in general, AI.
For questions related to the concept of neural (network) architecture search (NAS), which is a way of automating the design (that is, the hyper-parameters) of a neural network. NAS is related to neuro…
For questions related to the "crossover" operator (in the context of genetic algorithms).
For questions related to Bayesian networks, which are e.g. used to study causality (or causation) in AI.
For questions related to the concept of "return" in reinforcement learning.
For questions related to the book "Artificial Intelligence: A Modern Approach" by Peter Norvig and Stuart J. Russell.
For questions related to the family of models known as YOLO (which stands for "You Only Look Once"), which were proposed by Joseph Redmon et al. There are at least three YOLO models (versions 1, 2, an…