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 a neural networks, such as MLPs, CNNs, RNNs, LSTM networks, their variants or any other machine learning components that qualify as a neural networks in that they simulate a comple…
For questions about machine learning (ml) and the related concepts with respect to AI.
For questions about Deep Learning (also known as deep structured learning or hierarchical learning.)
For questions related to learning controlled by external positive reinforcement or negative feedback signal or both, where learning and use of what has been thus far learned occur concurrently.
For questions about convolutional neural networks, also known as CNN or ConvNet.
For questions related to successful or novel designing standards and procedures of Artificially Intelligent agents.
For questions about algorithm's that exhibit characteristics of intelligence, or are critical components in systems that exhibit intelligence, and problem-solving and goal-based algorithms in general.
the computer representation and manipulation of human languages that developed in social (rather than mathematical or other) contexts. Use the natural-language tag for q…
For questions about the image-recognition abilities of AI.
For questions related to the placement of individual cases into categories, such as is essential in fraud detection, spam detection, quality control, prediction of user or market responses, automated …
For questions about training networks, rules systems, or other AI system components.
Use for basic, fundamental questions about AI theory or practice. (i.e. design, application, implementation, mathematics of AI, philosophy of AI, etc.)
Use for questions related to AI implementation in the Python language
For questions about the application/possible applications of Machine Learning methods and Artificial Intelligence algorithms in the field of computer vision.
For questions related to Google's open source library for machine learning and machine intelligence.
For questions related to the philosophical aspects of artificial intelligence. Topics such as human/AI value alignment, artificial consciousness, the feasibility of AGI, the ethics of AI, Neo-Luddism,…
A method for solving constrained and unconstrained optimization problems based on natural selection processes. Use this tag for questions about GA; programming questions are off-topic. See https://ai.…
For questions related to in-depth study or academic research. Do NOT use this tag when you are trying to find something out.
For questions about deep neural networks (DNNs), neural networks with multiple hidden layers between the input and output layer.
Use for questions about Recurrent Neural Networks
For questions related to the technique of backpropagation, whereby the loss, error, or correction signal at an artificial neural network output is fed back to the sequence of network layer parameters …
For questions based on proper usage of data for Machine Learning ad other Algorithms to extract useful information.
Use on questions about getting started in AI. Ideal for those new to the field who want to begin researching and developing applications.
For questions related to Keras, the modular neural networks library written in Python
For questions related to the definition of and use of terminology in the context of Artificial Intelligence
For questions involving search algorithms and their use in artificial intelligence
Traditionally "Artificial General Intelligence", although more recently applied to "Strong Narrow AI"
For questions about LSTM (long-short term memory) networks.
For questions about implementing and improving optimization algorithms used in creating AI programs, or optimization in general.
Use for questions that involve Q-learning, where Q is the value of a particular next action among a set of possible actions, based on a specified function of each action and its projected result.
For questions about different learning algorithms used by a Machine Learning program to achieve its end goal.
For questions about algorithms recognizing individual objects represented by any/all of their physical characteristics.
For questions about algorithms that exhibit characteristics of evolution in that the structure, form, or processes of that which is evolving incrementally improves, either by DNA mutation and selectio…