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 related to machine translation (MT), which is the task of translating text using a computer, machine or software.
For questions related to the concept of feature selection (also known as variable selection or attribute selection), which is the process of selecting a subset of relevant features (a.k.a. variables o…
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.
Use for objective evaluations and assessments of computing devices and components, including CPUs, GPUs, etc., based on architecture and performance statistics. Opinions may be suitable for comm…
For questions about the application of AI/ML algorithms in the field of OCR.
For questions related to (automatic) text summarization, which is the task of producing a concise and fluent summary of a text or document while preserving key information content and the overall me…
Use for question about the emergent "mythology of AI", from Talos in Greek mythology, to Skynet and the technological singularity.
For questions related to Thomas Bayes, his work and extension of his work, theory and applications.
For questions related to the reinforcement learning algorithm called proximal policy optimization (PPO), which was introduced in the paper "Proximal Policy Optimization Algorithms" (2017) by John Schu…
For questions related to time series analysis or forecasting in the context of AI and, in particular, ML.
For questions related to the concept of hyper-parameter optimization, that is, the task of finding the best hyper-parameters for a particular learning algorithm (e.g. gradient descent) or model (e.g. …
For questions related to transfer learning, a machine learning method that focuses on storing knowledge gained while solving one problem in order to apply this knowledge to a different but related pro…
For questions related to the family of algorithms called "hill climbing" (in the context of AI).
For questions related to the temporal-difference reinforcement learning (RL) algorithms, which is a class of model-free (that is, they do not use the transition and reward function of the MDP) RL algo…
For questions related to the concept of environment in reinforcement learning and other AI sub-fields.
For questions related to the "experience replay" buffer (as used in the Deep Q Network and similar works).
Use for questions related to use of electronic circuits to mimic neuro-biological architectures present in the nervous system or in neural networks. ("Neuromorphic computing" is sometimes used synonom…
For questions related to attention based AI approaches, including gating at the network cell level, selection of models within a model container, virtual pan and zoom within an image field, selection …
For questions related to DeepMind's AlphaGo, which is the first computer Go program to beat a human professional Go player without handicaps on a full-sized 19x19 board. AlphaGo was introduced in the …
For questions about implementation of Machine Learning and Artificial Intelligence algorithms in the Java programming language.
For questions regarding various parameters/methods of implementation/improvement/analysing the safety of an Artificially Intelligent algorithm.
For questions about the use of Markov models in the field of AI/ML.
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).
An interdisciplinary field concerned with the statistical or rule-based modeling of natural language from a computational perspective.
For questions related to AlphaGo Zero, which is a version of DeepMind's Go software, AlphaGo, that does not use data from human games and it is stronger than AlphaGo. There is a generalized version of…
For questions related to recommender systems in the context of machine learning and data mining.
For questions related to features in the context of machine learning and, in general, AI.
For questions related to image segmentation (in computer vision and related AI fields).
For questions related to the convolution operation or convolutional layer (in the case of convolutional neural networks).
For questions related to model-based reinforcement learning algorithms.