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Machine learning strategy
Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source)
Active learning (machine learning)
Active_learning_(machine_learning)
Branch of machine learning
In machine learning, deep learning (DL) focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation
Deep_learning
Machine learning paradigm
In machine learning, supervised learning (SL) is a type of machine learning paradigm where an algorithm learns to map input data to a specific output based
Supervised_learning
Interdisciplinary research area
Quantum machine learning (QML) is the study of quantum algorithms for machine learning. It often refers to quantum algorithms for machine learning tasks
Quantum_machine_learning
machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Process of acquiring new knowledge
humans, other animals, and some machines. There is also evidence for some kind of learning in certain plants. Some learning is immediate, induced by a single
Learning
Educational software application
programs, materials, or learning and development programs. The learning management system concept emerged directly from e-Learning. Learning management systems
Learning_management_system
Machine learning technique
In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence
Attention_(machine_learning)
Memorization technique based on repetition
alternatives to rote learning include meaningful learning, associative learning, spaced repetition and active learning. Rote learning is widely used in the
Rote_learning
Decentralized machine learning
Federated learning (also known as collaborative learning) is a machine learning technique in a setting where multiple entities (often called clients)
Federated_learning
Phase transition in machine learning
In machine learning, grokking, or delayed generalization, is a phenomenon observed in some settings where a model abruptly transitions from overfitting
Grokking_(machine_learning)
Research field that lies at the intersection of machine learning and computer security
Adversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. Machine learning techniques
Adversarial_machine_learning
Subset of artificial intelligence
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn
Machine_learning
Measurable property or characteristic
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating
Feature_(machine_learning)
Overview of and topical guide to machine learning
outline is provided as an overview of, and topical guide to, machine learning: Machine learning (ML) is a subfield of artificial intelligence within computer
Outline_of_machine_learning
Plot of machine learning model performance over time or experience
In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and
Learning curve (machine learning)
Learning_curve_(machine_learning)
Ensemble learning method
In machine learning (ML), boosting is an ensemble learning method that combines a set of less accurate models (called "weak learners") to create a single
Boosting_(machine_learning)
Situation in which two or more people learn or attempt to learn something together
specifically, collaborative learning is based on the model that knowledge can be created within a population where members actively interact by sharing experiences
Collaborative_learning
Field of machine learning
Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. While supervised learning and
Reinforcement_learning
Process of automating the application of machine learning
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination
Automated_machine_learning
Theory and philosophy of learning
didactic learning, in which the learner plays a comparatively passive role. It is related to, but not synonymous with, other forms of active learning such
Experiential_learning
Paradigm in machine learning that uses no classification labels
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled
Unsupervised_learning
Machine learning method
Logic learning machine (LLM) is a machine learning method based on the generation of intelligible rules. LLM is an efficient implementation of the Switching
Logic_learning_machine
Machine learning technique
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related
Transfer_learning
Statistics and machine learning technique
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from
Ensemble_learning
Applications of machine learning to quantum physics
Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research. A basic example
Machine_learning_in_physics
Academic journal
The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the
Journal of Machine Learning Research
Journal_of_Machine_Learning_Research
Ongoing, voluntary, and self-motivated pursuit of knowledge
Lifelong learning is the "ongoing, voluntary, and self-motivated" pursuit of learning for either personal or professional reasons. Lifelong learning is important
Lifelong_learning
Method of machine learning
In computer science, incremental learning is a method of machine learning in which input data is continuously used to extend the existing model's knowledge
Incremental_learning
Machine learning technique
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Relationship between proficiency and experience
a learning curve Proficiency (test score)Experience (hours spent)01234503691215Proficiency (test score)Example of a steep learning curve A learning curve
Learning_curve
Method of machine learning
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update
Online_machine_learning
Set of learning techniques in machine learning
In machine learning (ML), feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations
Feature_learning
AI that learns decision rules from data
Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves
Rule-based_machine_learning
Set of methods for supervised statistical learning
In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms
Support_vector_machine
Concept in machine learning
In statistics and machine learning, leakage (also known as data leakage or target leakage) refers to the use of information during model training that
Leakage_(machine_learning)
Learning method
passive learning being the result or intended outcome of the instruction. This style of learning is teacher-centered and contrasts to active learning, which
Passive_learning
Use of machine learning to rank items
Learning to rank (LTR) or machine-learned ranking (MLR) is the application of machine learning, often supervised, semi-supervised or reinforcement learning
Learning_to_rank
Machine learning that combines deep learning and reinforcement learning
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem
Deep_reinforcement_learning
Machine learning for robots
Robot learning is a research field at the intersection of machine learning and robotics. It studies techniques allowing a robot to acquire novel skills
Robot_learning
Academic conference in machine learning
The International Conference on Machine Learning (ICML) is an international academic conference in machine learning held annually since 1980. It is the
International Conference on Machine Learning
International_Conference_on_Machine_Learning
Machine learning algorithm
Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or
Decision_tree_learning
Technique in machine learning
Curriculum learning is a technique in machine learning in which a model is trained on examples of increasing difficulty, where the definition of "difficulty"
Curriculum_learning
Paradigm in machine learning
Weak supervision (also known as semi-supervised learning) is a paradigm in machine learning, the relevance and notability of which increased with the
Weak_supervision
Learning by physical activities
Kinesthetic learning (American English), kinaesthetic learning (British English), or tactile learning is learning that involves physical activity. As
Kinesthetic_learning
Educational approach
facts and procedures. Authentic learning, on the other hand, takes a constructivist approach, in which learning is an active process. Teachers provide opportunities
Authentic_learning
Tuning parameter (hyperparameter) in optimization
In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration
Learning_rate
Use of technology in education to enhance learning and teaching
Networked Collaborative Learning: Social Interaction and Active Learning Archived 17 September 2018 at the Wayback Machine, Woodhead/Chandos Publishing
Educational_technology
Field of educational research
to play. Gee's video game learning theory includes his identification of thirty-six learning principles, including: 1) Active Control, 2) Design Principle
Games_and_learning
Concept in education and psychology
Dietze and Diane Kashin in Playing and Learning seven common characteristics of play include: Play is active. Play is child-initiated. Play is process-oriented
Learning_through_play
Educational practice of interaction among students
and learning. In his 1916 book, Democracy and Education, John Dewey wrote, "Education is not an affair of 'telling' and being told, but an active and
Peer_learning
Subfield of machine learning
Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of
Meta-learning (computer science)
Meta-learning_(computer_science)
Term in educational psychology
Concept learning, also known as category learning, concept attainment, and concept formation, is defined by Bruner, Goodnow, & Austin (1956) as "the search
Concept_learning
Group of people cooperating to achieve academic goals
happens in the community; that means, an active and not just a reactive performance (influence). Besides, a learning community must give a chance to the participants
Learning_community
Distance education using mobile device technology
M-learning, or mobile learning, is a form of distance education or technology enhanced active learning where learners use portable devices such as mobile
M-learning
Learning that occurs through observing the behaviour of others
Observational learning is learning that occurs through observing the behavior of others. It is a form of social learning which takes various forms, based
Observational_learning
Theory of knowledge
constructivism is often associated with pedagogic approaches that promote active learning, or learning by doing. While there is much enthusiasm for constructivism as
Constructivism (philosophy of education)
Constructivism_(philosophy_of_education)
Algorithm for modelling sequential data
In deep learning, the transformer is a family of artificial neural network architectures based on the multi-head attention mechanism, in which text is
Transformer_(deep_learning)
are a comparison of machine learning software such as software frameworks, libraries, and computer programs used for machine learning. Apache OpenNLP —
Comparison of machine learning software
Comparison_of_machine_learning_software
Framework for machine learning
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. Statistical learning theory
Statistical_learning_theory
Category of learning situation
Non-formal learning includes various structured learning situations which do not either have the level of curriculum, institutionalization, accreditation
Nonformal_learning
Solving multiple machine learning tasks at the same time
Multi-task learning (MTL) is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities
Multi-task_learning
Machine learning paradigm
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals
Self-supervised_learning
Process of learning better perception skills
Perceptual learning is the learning of perception skills, such as differentiating two musical tones from one another or categorizations of spatial and
Perceptual_learning
Learner centric pedagogy
teacher-centered passive learning although in practice it is used more in student-centered active learning environments, including inquiry-based learning, problem-based
Phenomenon-based_learning
Model-free reinforcement learning algorithm
Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring
Q-learning
Framework for mathematical analysis of machine learning
computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed
Probably approximately correct learning
Probably_approximately_correct_learning
Computational model used in machine learning
In machine learning, a neural network (NN) or neural net, is a computational model inspired by the structure and functions of biological neural networks
Neural network (machine learning)
Neural_network_(machine_learning)
Ability to learn vocalization
Vocal learning is the ability to modify acoustic and syntactic sounds, acquire new sounds via imitation, and produce vocalizations. "Vocalizations" in
Vocal_learning
Research field in deep learning
deep learning (TDL) is a research field that extends deep learning to handle complex, non-Euclidean data structures. Traditional deep learning models
Topological_deep_learning
Theory that describes how students receive, process, and retain knowledge during learning
Learning theory attempts to describe how students receive, process, and retain knowledge during learning. Cognitive, emotional, and environmental influences
Learning_theory_(education)
Tabular comparison of deep learning software
under different licenses [further explanation needed] Comparison of machine learning software Comparison of statistical packages Comparison of cognitive
Comparison of deep learning software
Comparison_of_deep_learning_software
Learning vocabulary in a second language
the term incidental vocabulary learning. Intentional vocabulary learning, active learning, and direct instruction are also used. However, the term deliberate
Vocabulary_learning
Theory of machine learning
Theoretical results in machine learning often focus on a type of inductive learning known as supervised learning. In supervised learning, an algorithm is provided
Computational_learning_theory
Machine learning technique
In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization
Normalization (machine learning)
Normalization_(machine_learning)
Automated recognition of patterns and regularities in data
retrieval, bioinformatics, data compression, computer graphics and machine learning. Pattern recognition has its origins in statistics and engineering;
Pattern_recognition
Optimization algorithm
become an important optimization method in machine learning. Both statistical estimation and machine learning consider the problem of minimizing an objective
Stochastic_gradient_descent
Academic discipline; examines how goal-driven social entities add and create knowledge
of innovations. Learning organizations are organizations that actively work to optimize learning. Learning organizations use the active process of knowledge
Organizational_learning
Deep learning artificial intelligence research team
to artificial intelligence. Formed in 2011, it combined open-ended machine learning research with information systems and large-scale computing resources
Google_Brain
Type of artificial neural network
learning machines are feedforward neural networks for classification, regression, clustering, sparse approximation, compression and feature learning with
Extreme_learning_machine
Machine learning methods using multiple input modalities
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images
Multimodal_learning
Extracting features from raw data for machine learning
Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set
Feature_engineering
Technique for the generative modeling of a continuous probability distribution
In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable
Diffusion_model
Educational approach aiming to promote learning by using video game design and elements
approach encourages students to explore their own learning processes through reflection and active participation, enabling them to adapt to new academic
Gamification_of_learning
Educational strategy
learning (SRL) is one of the domains of self-regulation, and is aligned most closely with educational aims. Broadly speaking, it refers to learning that
Self-regulated_learning
Method in machine learning
called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and
Bootstrap_aggregating
Action model learning (sometimes abbreviated action learning) is an area of machine learning concerned with the creation and modification of a software
Action_model_learning
Reinforcement learning method
prediction to overcome practical issues of deep active learning for named entity recognition". Machine Learning. 109 (9): 1749–1778. arXiv:1911.07335. doi:10
Error-driven_learning
Mode of delivering education to students who are not physically present
education (also known as online learning, remote learning or remote education) through an online school. A distance learning program can either be completely
Distance_education
Sub-field of reinforcement learning
Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that coexist
Multi-agent reinforcement learning
Multi-agent_reinforcement_learning
Model of algorithmic learning
In computational learning theory, Occam learning is a model of algorithmic learning where the objective of the learner is to output a succinct representation
Occam_learning
Statistical optimization technique
experimental design Probabilistic numerics Pareto optimum Active learning (machine learning) Multi-objective optimization Močkus, J. (1989). Bayesian
Bayesian_optimization
Movements that reflect nervous system changes
Motor learning refers broadly to changes in an organism's movements that reflect changes in the structure and function of the nervous system. Motor learning
Motor_learning
Learning technique
Augmented learning is an on-demand learning technique where the environment adapts to the learner. By providing remediation on-demand, learners can gain
Augmented_learning
Learning and teaching strategy
University School of Medicine, individuals who learned through an active team based learning curriculum had greater long-term knowledge retention compared
Team-based_learning
Intelligence of machines
develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize
Artificial_intelligence
Physical setting for a learning environment
passive or active learning, kinesthetic or physical learning, vocational learning, experiential learning, and others. As the design of a learning space impacts
Learning_space
Computer programming concept
Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate
Temporal_difference_learning
Learning technique
Computer-assisted language learning (CALL), known as computer-assisted learning (CAL) in British English and computer-aided language instruction (CALI)
Computer-assisted language learning
Computer-assisted_language_learning
Open-source software library developed by Yandex
available on GitHub. InfoWorld magazine awarded the library "The best machine learning tools" in 2017. along with TensorFlow, Pytorch, XGBoost and 8 other
CatBoost
ACTIVE LEARNING-MACHINE-LEARNING
ACTIVE LEARNING-MACHINE-LEARNING
Female
Yiddish
(×™Ö·×—Ö°× Ö¶×¢) Yiddish form of Hebrew Yochana, YACHNE means "God is gracious."Â
Male
Hebrew
Variant spelling of Hebrew Yakiyn, YACHIN means "he establishes" or "whom God strengthens."Â
Female
German
German form of Scottish Malvina, MALWINE means "smooth-brow."
Female
Scottish
Feminine form of Scottish Lachlan, LACHINA means "lake-land."
Girl/Female
Bengali, Indian
Machine
Girl/Female
Native American
Spirit.
Female
English
Feminine form of English Max, MAXINE means either "the greatest rival" or "the stream of Mack."Â
Male
French
French form of Latin Macarius, MACAIRE means "blessed."
Female
French
French feminine form of Latin Martinus, MARTINE means "of/like Mars."Â
Surname or Lastname
English
English : variant spelling of Lanning.
Boy/Male
American, Australian
Weighing Machine
Female
Hawaiian
Hawaiian name MAHINA means "moon; moonlight."
Male
Scottish
Pet form of Scottish Gaelic Lachlann, LACHIE means "lake-land."
Female
Native American
Native American Hopi name KACHINA means "sacred dancer; spirit."
Girl/Female
Australian, Japanese
Child of Machi
Male
English
Pet form of English Sacheverell, SACHIE means "roe-buck leap."
Female
English
Variant spelling of English Maureen, MAURINE means "obstinacy, rebelliousness" or "their rebellion."
Female
French
Feminine form of French Marin, MARINE means "of the sea."
Male
Hindi/Indian
(सचिन) Hindi myth name borne by Indra, SACHIN means "pure."
Surname or Lastname
English
English : variant spelling of Machen.Spanish (MachÃn) : probably a nickname from machÃn ‘boor’, ‘lout’, often applied to a blacksmith’s apprentice.French : nickname from Old French machin ‘scheming’.
ACTIVE LEARNING-MACHINE-LEARNING
ACTIVE LEARNING-MACHINE-LEARNING
Boy/Male
Indian
Leader, President, Head, Chief
Boy/Male
Tamil
Dhrumil | தà¯à®°à¯à®®à¯€à®²Â
Nil
Girl/Female
Bengali, Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Sanskrit, Sindhi, Telugu, Traditional
The Only Child
Boy/Male
American, Australian, British, Chinese, English, Scottish
Son of the Strong One; Variant of Bryce
Male
Turkish
Turkish name BULUT means "cloud."
Boy/Male
Indian, Punjabi, Sikh
Coastal Victory
Girl/Female
Scandinavian
Abbreviation of Katherine. Pure.
Boy/Male
Tamil
Immoveable, Firm, Unshakeable, Constant
Boy/Male
British, English
Lover
Boy/Male
Tamil
Lord Ganesha
ACTIVE LEARNING-MACHINE-LEARNING
ACTIVE LEARNING-MACHINE-LEARNING
ACTIVE LEARNING-MACHINE-LEARNING
ACTIVE LEARNING-MACHINE-LEARNING
ACTIVE LEARNING-MACHINE-LEARNING
v. t.
To subject to the action of machinery; to effect by aid of machinery; to print with a printing machine.
imp. & p. p.
of Machine
a.
Acting in concurrence; united in action.
n.
One who or operates a machine; a machinist.
n.
Machines, in general, or collectively.
n.
A combination of persons acting together for a common purpose, with the agencies which they use; as, the social machine.
n.
The acquisition of knowledge or skill; as, the learning of languages; the learning of telegraphy.
n.
The parts by which motion imparted to one portion of an engine or machine is transmitted to another, considered collectively; as, the valve gearing of locomotive engine; belt gearing; esp., a train of wheels for transmitting and varying motion in machinery.
a.
Having the power or quality of acting; causing change; communicating action or motion; acting; -- opposed to passive, that receives; as, certain active principles; the powers of the mind.
adv.
In an active signification; as, a word used actively.
pl.
of Earning
a.
Given to action rather than contemplation; practical; operative; -- opposed to speculative or theoretical; as, an active rather than a speculative statesman.
a.
Guiding; directing; controlling; foremost; as, a leading motive; a leading man; a leading example.
a.
Requiring or implying action or exertion; -- opposed to sedentary or to tranquil; as, active employment or service; active scenes.
a.
In action; actually proceeding; working; in force; -- opposed to quiescent, dormant, or extinct; as, active laws; active hostilities; an active volcano.
a.
Brisk; lively; as, an active demand for corn.
n.
The knowledge or skill received by instruction or study; acquired knowledge or ideas in any branch of science or literature; erudition; literature; science; as, he is a man of great learning.
a.
Given to action; constantly engaged in action; energetic; diligent; busy; -- opposed to dull, sluggish, indolent, or inert; as, an active man of business; active mind; active zeal.
n.
The working parts of a machine, engine, or instrument; as, the machinery of a watch.
a.
Implying or producing rapid action; as, an active disease; an active remedy.