Competition-based learning (CBL) is a student-centered pedagogy that combines project-based learning and competitions. This can sometimes be referred...

Design-based learning (DBL), also known as design-based instruction, is an inquiry-based form of learning, or pedagogy, that is based on integration of...

since April 2012 Integration Bee — competition in integral calculus held in various institutions of higher learning in the United States and some other...

person's height based on factors like age and genetics or forecasting future temperatures based on historical data. Similarity learning is an area of supervised...

models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science...

Learning to rank or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning...

page is a timeline of machine learning. Major discoveries, achievements, milestones and other major events in machine learning are included. History of artificial...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

The Noetic Learning math contest is a national biannual problem-solving competition for elementary and middle school students. The contest aims to encourage...

Cooperative learning is an educational approach which aims to organize classroom activities into academic and social learning experiences. There is much...

The Makridakis Competitions (also known as the M Competitions or M-Competitions) are a series of open competitions to evaluate and compare the accuracy...

Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression...

intended to leverage people's evolved desires for socializing, learning, mastery, competition, achievement, status, self-expression, altruism, or closure...

Active learning is "a method of learning in which students are actively or experientially involved in the learning process and where there are different...

D. O. Hebb proposed a learning hypothesis based on the mechanism of neural plasticity that became known as Hebbian learning. It was used in many early...

in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary...

Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based on various...

William Lowell Putnam Mathematical Competition, often abbreviated to Putnam Competition, is an annual mathematics competition for undergraduate college students...

including text, images and audio. Convolution-based networks are the de-facto standard in deep learning-based approaches to computer vision and image processing...

Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set...

Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist...

education (also known as online learning, remote learning or remote education) through an online school. A distance learning program can either be completely...

control, procedural content generation (PCG) and deep learning-based content generation. Machine learning is a subset of artificial intelligence that uses...

that uses spaced repetition of flashcards to increase the rate of learning. It is based in London, UK. Memrise offers user-generated content on a wide range...

Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. A survey from May 2020...

finding clusters within data. Models and algorithms based on the principle of competitive learning include vector quantization and self-organizing maps...

Kinesthetic learning (American English), kinaesthetic learning (British English), or tactile learning is learning that involves physical activity. As...

to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field...

ChatGPT are often based on large language models called generative pre-trained transformers (GPT). They are based on a deep learning architecture called...

a learning hypothesis based on the mechanism of neural plasticity that became known as Hebbian learning. Hebbian learning is unsupervised learning. This...