Apriori Algorithm- https://www.engati.com/glossary/apriori-algorithm
Apriori algorithm helps find frequent or repetitive item sets in a database based on associations between the presence or absence of items.
Admissible heuristic- https://www.engati.com/glossary/admissible-heuristic
Admissible heuristics are used to estimate the cost of reaching the goal state in a search algorithm, always finding the cheapest path solution.
Speech-to-text Translation- https://www.engati.com/glossary/speech-to-text-translation
Speech-to-text conversion is converting spoken words into written texts. It lets you type with your voice, to improve your workflow and efficiency.
Non-deterministic algorithm- https://www.engati.com/glossary/non-deterministic-algorithm
A nondeterministic algorithm is an algorithm that exhibits different behaviors on different runs, as opposed to a deterministic algorithm.
Temporal difference learning- https://www.engati.com/glossary/temporal-difference-learning
Temporal Difference Learning is a learning technique commonly used in reinforcement learning to predict the total reward expected over the future
Lexical-Functional Grammar- https://www.engati.com/glossary/lexical-functional-grammar
Lexical functional grammar (LFG) is a constraint-based grammar framework in theoretical linguistics used for analysis of language.
Ridge Regression- https://www.engati.com/glossary/ridge-regression
Ridge regression is a fundamental regularization technique, but it is not used very widely because of the complex science behind it.
Brute-force search- https://www.engati.com/glossary/brute-force-search
Brute-force search is a problem-solving method that uses computing power to test every possible solution to improve system efficiency.
Human-Computer Interaction (HCI)- https://www.engati.com/glossary/human-computer-interaction
Human-Computer Interaction is the study of people interacting with computers. With academics, HCI can be used in the field of User Experience too.
Bag of words Model- https://www.engati.com/glossary/bag-of-words
The bag-of-words (bow) model is used to preprocess the text by converting it into a bag of words or fixed-length vectors, using machine learning algorithm.
Chatbot Avatar- https://www.engati.com/glossary/chatbot-avatar
Chatbot Avatar is a computer-generated character representing a real-life person, concept, or an artificial entity on the website.
Approximation Error- https://www.engati.com/glossary/approximation-error
Approximation error in some data is the discrepancy between an exact value and some approximation to it. It can happen due to measurement issues.
Predicate logic- https://www.engati.com/glossary/predicate-logic
Predicate logic is a mathematical model that is used for reasoning with predicates. Predicates are functions that map variables to truth values.
Average Response Time- https://www.engati.com/glossary/average-response-time
Average Response Time is the time taken by a representative to respond to a customer after they have voiced a request or a concern.
Rule-Based System- https://www.engati.com/glossary/rule-based-system
Rule-based systems are the simplest forms of AI. A rule-based system uses rules since it has the data illustration for knowledge coded into the system
Computational statistics- https://www.engati.com/glossary/computational-statistics
Computational statistics or statistical computing focuses on the bond between statistics and computer science to transform raw data into knowledge.
Autonomic computing- https://www.engati.com/glossary/autonomic-computing
Autonomic computing refers to the self-managing characteristics of distributed computing resources while hiding intrinsic complexity to operators.
Discourse analysis- https://www.engati.com/glossary/discourse-analysis
Discourse analysis is a research method that is used for the purpose of studying written or spoken language in relation to its social context.
Logical Deduction- https://www.engati.com/glossary/logical-deduction
Deductive reasoning, also know as deductive logic, is the process of reasoning from one or more statements (premises) to reach a logical conclusion.
Lazy learning- https://www.engati.com/glossary/lazy-learning
Lazy learning refers to machine learning processes in which generalization of the training data is delayed until a query is made to the system