"Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive."
The development of software that can learn from data and make decisions or predictions based on that data, using machine learning or other techniques.
Machine learning: The study of algorithms and statistical models that enable software applications to learn and improve from experience without being explicitly programmed.
Deep learning: A subset of machine learning that deals with artificial neural networks that can simulate and learn like humans.
Natural Language Processing (NLP): A subfield of AI concerned with enabling computers to understand and generate human language.
Computer Vision: The study of algorithms and systems for acquiring, processing, analyzing, and understanding images or visual data from the world in order to produce numerical or symbolic information.
Robotics: The study of robotics involves the design, construction, operation, and use of robots, as well as computer systems for their control, sensory feedback, and information processing.
Artificial General Intelligence (AGI): The study of creating machines that are capable of performing any intellectual task that a human can do.
Evolutionary Computation: The study of algorithms and models that simulate natural selection and evolution in order to optimize various tasks.
Expert Systems: AI systems that imitate the decision-making ability of a human expert in a specific domain.
Knowledge Representation and Reasoning: The study of how to represent knowledge in a computer in a form that is useful for reasoning, querying, and learning.
Reinforcement Learning: A machine learning technique that enables an agent to learn by interacting with the environment through trial and error.
Bayesian Networks: A probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph.
Swarm Intelligence: A branch of AI inspired by the collective behavior of insects, birds, and other animals that can solve complex problems by cooperating with each other.
Fuzzy Logic: A mathematical logic that deals with uncertainty and imprecision by assigning degrees of truth to statements rather than binary values.
Constraint Satisfaction: The study of how to solve constraint satisfaction problems, which are computational problems that involve finding values for set of variables that satisfy a set of constraints.
Genetic Algorithms: A type of evolution-based optimization algorithm that can be applied to almost any problem for which a fitness function can be defined.
Rule-Based Systems (Expert Systems): It is an AI system that makes decisions based on a set of predefined rules. It is mostly used in the field of engineering, finance, and healthcare.
Machine Learning: It is a type of AI where computer algorithms improve automatically through experience. It is commonly used in advertising, fraud detection, and recommendation systems.
Natural Language Processing (NLP): It is a type of AI that enables computers to understand, interpret, and generate human language. It has many applications, including chatbots, virtual assistants, and language translation.
Robotics: It is AI applied to robotics, and it enables robots to see, move, and communicate using sensors and algorithms.
Computer Vision: It is an AI technology that enables computers to interpret and analyze visual data from the world, such as images and videos. It is used in various fields, including security, healthcare, and transportation.
Cognitive Computing: It is a type of AI that simulates human thought processes, including reasoning, problem-solving, and language processing. It is used in various industries, including healthcare, education, and finance, to facilitate decision-making and automate tasks.
Deep Learning: It is a subset of machine learning that enables computers to learn and improve from experience by using neural networks. It is used in various fields, including image and speech recognition, fraud detection, and autonomous vehicles.
Game Playing: It is a type of AI that enables machines to play games against humans or other machines. It is used in video games, board games, and other game-related applications.
Swarm Intelligence: It is a type of AI that enables groups of machines to work together in a coordinated and intelligent manner. It is used in robotics, transportation, and logistics to optimize performance and minimize cost.
Expert Systems: It is an AI system that uses knowledge and rules to solve complex problems in a particular domain. It is used in various industries, including healthcare, finance, and manufacturing.
"the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms."
"Recently, generative artificial neural networks have been able to surpass results of many previous approaches."
"Machine-learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine."
"where it is too costly to develop algorithms to perform the needed tasks."
"The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods."
"Data mining is a related (parallel) field of study, focusing on exploratory data analysis through unsupervised learning."
"ML is known in its application across business problems under the name predictive analytics."
"Although not all machine learning is statistically based, computational statistics is an important source of the field's methods."
"the problems are solved by helping machines 'discover' their 'own' algorithms without needing to be explicitly told what to do by any human-developed algorithms."
"Machine-learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine."
"development of algorithms by human programmers would be cost-prohibitive"
"generative artificial neural networks have been able to surpass results of many previous approaches."
"Data mining is a related (parallel) field of study, focusing on exploratory data analysis through unsupervised learning."
"Machine-learning approaches have been applied to...medicine."
"helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms."
"the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms."
"The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods."
"where it is too costly to develop algorithms to perform the needed tasks."
"Although not all machine learning is statistically based, computational statistics is an important source of the field's methods."