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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
Computational model used in machine learning
Machine learning has involved a variety of approaches to training models, including supervised learning, unsupervised learning, reinforcement learning, and
Neural network (machine learning)
Neural_network_(machine_learning)
Set of learning techniques in machine learning
explicit algorithms. Feature learning can be either supervised, unsupervised, or self-supervised: In supervised feature learning, features are learned using
Feature_learning
Subset of artificial intelligence
foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysis (EDA) through unsupervised learning. From a theoretical
Machine_learning
"Large-scale deep unsupervised learning using graphics processors". Proceedings of the 26th Annual International Conference on Machine Learning. ICML '09. New
History of artificial neural networks
History_of_artificial_neural_networks
Machine learning paradigm
Next, the actual task is performed with supervised or unsupervised learning. Self-supervised learning has produced promising results in recent years, and
Self-supervised_learning
Algorithm for modelling sequential data
2026-04-05. Retrieved 2026-05-16. "Improving language understanding with unsupervised learning". openai.com. June 11, 2018. Archived from the original on 2023-03-18
Transformer_(deep_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
Data analysis techniques for fraud detection
The machine learning and artificial intelligence solutions may be classified into two categories: 'supervised' and 'unsupervised' learning. These methods
Data analysis for fraud detection
Data_analysis_for_fraud_detection
Branch of computer science
analysis to discover vulnerabilities or enhance compatibility. Unsupervised learning is utilized to detect concealed patterns and structures in untagged
AI-assisted reverse engineering
AI-assisted_reverse_engineering
Paradigm in machine learning
time-consuming supervised learning paradigm), followed by a large amount of unlabeled data (used exclusively in unsupervised learning paradigm). In other words
Weak_supervision
Type of large language model
Retrieved April 29, 2023. "Improving language understanding with unsupervised learning". openai.com. June 11, 2018. Archived from the original on March
Generative pre-trained transformer
Generative_pre-trained_transformer
Branch of biology
wide range of software and algorithms to carry out their research. Unsupervised learning is a type of algorithm that finds patterns in unlabeled data. One
Computational_biology
Image-generating machine learning model
Learning (2 ed.). O'Reilly. Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, Surya Ganguli (March 12, 2015). "Deep Unsupervised Learning using
Stable_Diffusion
Branch of machine learning
network. Methods used can be supervised, semi-supervised or unsupervised. Some common deep learning network architectures include fully connected networks
Deep_learning
Technique for the generative modeling of a continuous probability distribution
"Deep Unsupervised Learning using Nonequilibrium Thermodynamics" (PDF). Proceedings of the 32nd International Conference on Machine Learning. 37. PMLR:
Diffusion_model
Academic conference in machine learning
International Conference on Machine Learning (ICML) is an international academic conference in machine learning held annually since 1980. It is the oldest
International Conference on Machine Learning
International_Conference_on_Machine_Learning
Structuring text as input to generative artificial intelligence
David; Amodei, Dario; Sutskever, Ilya (2019). "Language Models are Unsupervised Multitask Learners" (PDF). OpenAI. Archived (PDF) from the original on
Prompt_engineering
Overview of and topical guide to machine learning
Application of statistics Supervised learning, where the model is trained on labeled data Unsupervised learning, where the model tries to identify patterns
Outline_of_machine_learning
Tree-based ensemble machine learning methods
Wisconsin. CiteSeerX 10.1.1.153.9168. Shi, T.; Horvath, S. (2006). "Unsupervised Learning with Random Forest Predictors". Journal of Computational and Graphical
Random_forest
Automated recognition of patterns and regularities in data
describe the corresponding supervised and unsupervised learning procedures for the same type of output. The unsupervised equivalent of classification is normally
Pattern_recognition
Type of feedforward neural network
"Large-scale deep unsupervised learning using graphics processors" (PDF). Proceedings of the 26th Annual International Conference on Machine Learning. ICML '09:
Convolutional_neural_network
Theory in neuropsychology
number of artificial neural network models which use supervised and unsupervised learning methods, and address problems such as pattern recognition and prediction
Adaptive_resonance_theory
British-Canadian computer scientist (born 1947)
"sleep" phases. In 2007, Hinton coauthored an unsupervised learning paper titled Unsupervised learning of image transformations. In 2008, he developed
Geoffrey_Hinton
Creation and use of user profiles via data analysis
data. This is called unsupervised learning. Two things are important with regard to this distinction. First, unsupervised learning algorithms seem to allow
Profiling (information science)
Profiling_(information_science)
2018 text-generating language model
contrast, a GPT's "semi-supervised" approach involved two stages: an unsupervised generative "pre-training" stage in which a language modeling objective
GPT-1
Machine learning researcher at Berkeley
has published numerous articles on reinforcement learning, robot learning, and unsupervised learning. Also in 2016, he became co-director of the Berkeley
Pieter_Abbeel
Machine learning paradigm
of datasets for machine-learning research Unsupervised learning Mitchell, Tom M. (2013). Machine learning. McGraw-Hill series in Computer Science (Nachdr
Supervised_learning
Machine learning model training problem
networks (Schmidhuber, 1992), pre-trained one level at a time through unsupervised learning, fine-tuned through backpropagation. Here each level learns a compressed
Vanishing_gradient_problem
Machine learning technique
feedback, learning a reward model, and optimizing the policy. Compared to data collection for techniques like unsupervised or self-supervised learning, collecting
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Academic conference in machine learning
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year.
International Conference on Learning Representations
International_Conference_on_Learning_Representations
Type of database that uses vectors to represent other data
from the raw data using machine learning methods such as feature extraction algorithms, word embeddings or deep learning networks. The goal is that semantically
Vector_database
Image-generating machine learning model
"High-Resolution Image Synthesis with Latent Diffusion Models". Computer Vision & Learning Group. Archived from the original on 16 November 2024. Retrieved 17 November
Flux_(text-to-image_model)
Artificial intelligence model paradigm
variable representing any text, image, sound, etc.), is a machine learning or deep learning model trained on vast datasets so that it can be applied across
Foundation_model
American computer scientist and software engineer
ended with "the cat neuron paper", a deep belief network trained by unsupervised learning on YouTube videos. This project morphed into Google Brain, a team
Jeff_Dean
Type of feedforward neural network
In deep learning, a multilayer perceptron (MLP) is a kind of modern feedforward neural network consisting of fully connected neurons with nonlinear activation
Multilayer_perceptron
Vietnamese-American computer scientist (born 1982)
is best known for his pioneering work in deep learning, particularly in large-scale unsupervised learning, sequence-to-sequence (seq2seq) models, and AutoML
Quoc_V._Le
Use of artificial intelligence in the automation of electronic design
supervised learning, unsupervised learning, reinforcement learning, and generative AI. Supervised learning is a type of machine learning where algorithms
AI-driven_design_automation
Unsupervised learning algorithm
The wake-sleep algorithm is an unsupervised learning algorithm for deep generative models, especially Helmholtz Machines. The algorithm is similar to
Wake-sleep_algorithm
do not need to be labeled, high-quality unlabeled datasets for unsupervised learning can also be difficult and costly to produce. Many organizations
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Algorithm for obtaining vector representations of words
is a model for distributed word representation. The model is an unsupervised learning algorithm for obtaining vector representations of words. This is
GloVe
Artificial neural network that mimics neurons
requirements limit their use. Although unsupervised biologically inspired learning methods are available such as Hebbian learning and STDP, no effective supervised
Spiking_neural_network
Identification of which sense of a word is being used
and completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have
Word-sense_disambiguation
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
image segmentation Dlib — C++ machine learning and computer vision library ELKI — data mining and unsupervised learning software fastText — Word embeddings
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
Deep learning architecture
Mamba is a deep learning architecture focused on sequence modeling. It was developed by two researchers Albert Gu from Carnegie Mellon University and Tri
Mamba (deep learning architecture)
Mamba_(deep_learning_architecture)
Intelligence of machines
machine learning. Unsupervised learning analyzes a stream of data and finds patterns and makes predictions without any other guidance. Supervised learning requires
Artificial_intelligence
Set of methods for supervised statistical learning
categorize unlabeled data.[citation needed] These data sets require unsupervised learning approaches, which attempt to find natural clustering of the data
Support_vector_machine
Game-playing artificial intelligence
advancement over AlphaZero, and a generalizable step forward in unsupervised learning techniques. The work was seen as advancing understanding of how
MuZero
Paradigm of rule-based machine learning methods
computation) with a learning component (performing either supervised learning, reinforcement learning, or unsupervised learning). Learning classifier systems
Learning_classifier_system
Class of artificial neural network
trained using skip connections. The neural history compressor is an unsupervised stack of RNNs. At the input level, it learns to predict its next input
Recurrent_neural_network
Type of machine learning model
performance via collaborative platforms such as Hugging Face. As machine learning algorithms process numbers rather than text, the text must be converted
Large_language_model
Approach in data analysis
number and variety of domains, and is an important subarea of unsupervised machine learning. As such it has applications in cyber-security, intrusion detection
Anomaly_detection
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)
Concept in machine learning
Rosset, Saharon (September 2022). "On the Cross-Validation Bias due to Unsupervised Preprocessing". Journal of the Royal Statistical Society Series B: Statistical
Leakage_(machine_learning)
Deep learning generative model to encode data representation
initially designed for unsupervised learning, its effectiveness has been proven for semi-supervised learning and supervised learning. A variational autoencoder
Variational_autoencoder
Representation learning method
dictionary learning has been successfully applied to various image, video and audio processing tasks as well as to texture synthesis and unsupervised clustering
Sparse_dictionary_learning
Interdisciplinary research area
Gilles; Gambs, Sébastien (2013-02-01). "Quantum speed-up for unsupervised learning". Machine Learning. 90 (2): 261–287. doi:10.1007/s10994-012-5316-5. ISSN 0885-6125
Quantum_machine_learning
Concept involving online bot activity
Retrieved June 16, 2023. "Improving language understanding with unsupervised learning". openai.com. Archived from the original on March 18, 2023. Retrieved
Dead_Internet_theory
Statistical tool to assess investments
proposes three techniques to clustering similar strategies using unsupervised learning techniques: The Optimal Number of Clusters (ONC) algorithm. Hierarchical
Deflated_Sharpe_ratio
2017 research paper by Google
Retrieved 16 May 2026. "Improving language understanding with unsupervised learning". openai.com. 11 June 2018. Archived from the original on 18 March
Attention_Is_All_You_Need
Neuroscientific theory
cognitive function, it is often regarded as the neuronal basis of unsupervised learning. Hebbian theory provides an explanation for how neurons might connect
Hebbian_theory
Table layout for visualizing performance; also called an error matrix
sounds. In machine learning these matrices show the success of the learning system both in supervised learning and unsupervised learning, where they are
Confusion_matrix
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
Automatic creation of ontologies
extracted concepts in a taxonomic structure. This is mostly achieved with unsupervised hierarchical clustering methods. Because the result of such methods is
Ontology_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
Framework for machine learning
prediction. Learning falls into many categories, including supervised learning, unsupervised learning, online learning, and reinforcement learning. From the
Statistical_learning_theory
Class of artificial neural networks
passing" for such approaches. In the more general subject of "geometric deep learning", certain existing neural network architectures can be interpreted as GNNs
Graph_neural_network
Node graph framework
Vinay; Anand, Avishek (2020). "A Comparative Study for Unsupervised Network Representation Learning". IEEE Transactions on Knowledge and Data Engineering:
Node2vec
Neural network that learns efficient data encoding in an unsupervised manner
neural network used to learn efficient codings of unlabeled data (unsupervised learning). An autoencoder learns two functions: an encoding function that
Autoencoder
Statistics and machine learning technique
as well. By analogy, ensemble techniques have been used also in unsupervised learning scenarios, for example in consensus clustering or in anomaly detection
Ensemble_learning
Deep learning method
model for unsupervised learning, GANs have also proved useful for semi-supervised learning, fully supervised learning, and reinforcement learning. The core
Generative adversarial network
Generative_adversarial_network
Smooth approximation of one-hot arg max
Processing series. MIT Press. ISBN 978-0-26202617-8. "Unsupervised Feature Learning and Deep Learning Tutorial". ufldl.stanford.edu. Retrieved 2024-03-25
Softmax_function
Ensemble learning method
object categories and their locations in images can be discovered in an unsupervised manner as well. The recognition of object categories in images is a challenging
Boosting_(machine_learning)
Fundamental unit of cognition
absent in unsupervised learning, such as forming concepts of different music genres without explicit labels or guidance. Semisupervised learning is an intermediate
Concept
Vector quantization algorithm minimizing the sum of squared deviations
shapes. The unsupervised k-means algorithm has a loose relationship to the k-nearest neighbor classifier, a popular supervised machine learning technique
K-means_clustering
Diffusion model over latent embedding space
"Deep Unsupervised Learning using Nonequilibrium Thermodynamics" (PDF). Proceedings of the 32nd International Conference on Machine Learning. 37. PMLR:
Latent_diffusion_model
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
Online service for AI media creation
paid service reliant on a diffusion model, while the original machine learning training data consists of images used without the consent of the original
NovelAI
Biological theory of intelligence
Subutai; Hawkins, Jeff (2016). "Continuous Online Sequence Learning with an Unsupervised Neural Network Model". Neural Computation. 28 (11): 2474–2504
Hierarchical_temporal_memory
Image-generating deep learning model
Jeffrey; Child, Rewon; et al. (14 February 2019). "Language models are unsupervised multitask learners" (PDF). cdn.openai.com. 1 (8). Archived (PDF) from
DALL-E
Reverse-engineering neural networks
identify structures, circuits or algorithms encoded in the weights of machine learning models. This contrasts with earlier interpretability methods that focused
Mechanistic_interpretability
Method for discovering interesting relations between variables in databases
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended
Association_rule_learning
ITU-T Recommendation
Apart from SL methods, other branches of ML such as Unsupervised Learning (UL) and Reinforcement Learning (RL) deal with uncertainty in one way or another
Y.3181
Conversational software
would behave as a conversational partner. Such chatbots often use deep learning and natural language processing. Simpler chatbots have existed for decades
Chatbot
Type of artificial neural network
these early efforts did not lead to a working learning algorithm for hidden units, i.e., deep learning. In 1965, Alexey Grigorevich Ivakhnenko and Valentin
Feedforward_neural_network
Erroneous AI-generated content
various ways); changes in the training process, such as using reinforcement learning; and post-processing methods that can correct hallucinations in the output
Hallucination (artificial intelligence)
Hallucination_(artificial_intelligence)
Programming library
for learning of word embeddings and text classification created by Facebook's AI Research (FAIR) lab. The model allows one to create an unsupervised learning
FastText
Method of machine learning
the model. It represents a dynamic technique of supervised learning and unsupervised learning that can be applied when training data becomes available gradually
Incremental_learning
Grouping a set of objects by similarity
applications, clustering is the driving force behind machine learning's unsupervised learning, and is embedded in systems ranging from search engines to
Cluster_analysis
Integrated circuit technology
digital, or mixed-mode VLSI, prioritize robustness, adaptability, and learning by emulating the brain’s distributed processing across small computing
Neuromorphic_computing
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
Model-free reinforcement learning algorithm
the episode. Therefore, calculating advantage is essentially an unsupervised learning problem. The baseline estimate comes from the value function that
Proximal_policy_optimization
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
2025 multimodal model by OpenAI
training process involved three stages: unsupervised pretraining, supervised fine-tuning, and reinforcement learning from human feedback. Pretraining used
GPT-5
January. 196B + 1.8B (ViT) "Improving language understanding with unsupervised learning". openai.com. June 11, 2018. Archived from the original on 2023-03-18
List_of_large_language_models
Class of artificial neural network
feature learning, topic modelling, immunology, and even many‑body quantum mechanics. They can be trained in either supervised or unsupervised ways, depending
Restricted_Boltzmann_machine
Technique in machine learning
"Baby Steps: How "Less is More" in unsupervised dependency parsing" (PDF). Retrieved March 29, 2024. "Self-paced learning for latent variable models". 6 December
Curriculum_learning
Quoc V. (2013). "Building high-level features using large scale unsupervised learning". 2013 IEEE International Conference on Acoustics, Speech and Signal
Timeline_of_machine_learning
Form of unsupervised learning in artificial neural networks
Competitive learning is a form of unsupervised learning in artificial neural networks, in which nodes compete for the right to respond to a subset of
Competitive_learning
UNSUPERVISED LEARNING
UNSUPERVISED LEARNING
Girl/Female
Tamil
Goddess of learning, Saraswati
Girl/Female
Tamil
Goddess of learning, Saraswati
Girl/Female
Tamil
Learning
Boy/Male
Tamil
Vidaysagar | விதாயà¯à®¸à®¾à®•à®°
Learning ocean
Vidaysagar | விதாயà¯à®¸à®¾à®•à®°
Boy/Male
Tamil
Vidyasagar | விதà¯à®¯à®¾à®¸à®¾à®•à®°Â
Ocean of learning
Vidyasagar | விதà¯à®¯à®¾à®¸à®¾à®•à®°Â
Girl/Female
Tamil
Saraswati | ஸரஸà¯à®µà®¤à¯€
Goddess Saraswati, Tamil Goddess for education, Goddess of learning
Saraswati | ஸரஸà¯à®µà®¤à¯€
Girl/Female
Tamil
Vidyasri | விதà¯à®¯à®¾à®¸à®°à¯€
Wisdom, Knowledge, Learning, Goddess Durga
Vidyasri | விதà¯à®¯à®¾à®¸à®°à¯€
Girl/Female
Tamil
Vidhya | விதà¯à®¯à®¾,விதà¯à®¯à®¾Â
Knowledge, Learning
Vidhya | விதà¯à®¯à®¾,விதà¯à®¯à®¾Â
Boy/Male
Muslim
Excellent, Eminent in learning (1)
Girl/Female
Sikh
Knowledge, Learning
Boy/Male
Indian
Excellent, Eminent in learning
Girl/Female
Tamil
Goddess of learning, Goddess Saraswati
Girl/Female
Tamil
Sarasvati | ஸரஸà¯à®µà®¤à¯€
A Goddess of learning
Sarasvati | ஸரஸà¯à®µà®¤à¯€
Boy/Male
Muslim
Excellent, Eminent in learning
Girl/Female
Tamil
Vaagdevi | வாகà¯à®¤à¯‡à®µà¯€
Goddess of learning, Saraswati
Vaagdevi | வாகà¯à®¤à¯‡à®µà¯€
Surname or Lastname
English, French, German, Hungarian (Donát), Polish, and Czech (Donát)
English, French, German, Hungarian (Donát), Polish, and Czech (Donát) : from a medieval personal name (Latin Donatus, past participle of donare, frequentative of dare ‘to give’). The name was much favored by early Christians, either because the birth of a child was seen as a gift from God, or else because the child was in turn dedicated to God. The name was borne by various early saints, among them a 6th-century hermit of Sisteron and a 7th-century bishop of Besançon, all of whom contributed to the popularity of the baptismal name in the Middle Ages, which was not checked by the heresy of a 4th-century Carthaginian bishop who also bore it. Another bearer was a 4th-century gramMarian and commentator on Virgil, widely respected in the Middle Ages as a figure of great learning.
Girl/Female
Tamil
Saraswathi | ஸரஸà¯à®µà®¾à®¤à¯€Â
Goddess Saraswati, Tamil Goddess for education, Goddess of learning
Saraswathi | ஸரஸà¯à®µà®¾à®¤à¯€Â
Girl/Female
Tamil
Saraswathy | ஸரஸà¯à®µà®¾à®¤à¯€ Â
Goddess Saraswati, Tamil Goddess for education, Goddess of learning
Saraswathy | ஸரஸà¯à®µà®¾à®¤à¯€ Â
Girl/Female
Tamil
Goddess of learning, Saraswati
Girl/Female
Tamil
Vidhyavathi | விதà¯à®¯à®¾à®µà®¾à®¤à¯€
Wisdom, Knowledge, Learning, Goddess Durga
UNSUPERVISED LEARNING
UNSUPERVISED LEARNING
Girl/Female
French, German, Latin
From Sebastia
Boy/Male
Tamil
Antariksh | அஂதரிகà¯à®·
Space
Female
Slovene
Slovene form of Greek Elisabet, ELIZABETA means "God is my oath."
Boy/Male
Arabic, Muslim
The Righteousness of the Faith
Boy/Male
Indian, Punjabi, Sikh
Victory of the Beloved
Girl/Female
Arabic, Basque
A Small Girl; Bird
Boy/Male
Muslim/Islamic
Intelligent skillful
Male
German
German form of Gothic Odovacar, OTTOKAR means "watchful of wealth."
Girl/Female
Tamil
Thejovathy | தேஜோவாதà¯à®¯
Goddess Durga
Boy/Male
Hindu, Indian, Tamil
Younger
UNSUPERVISED LEARNING
UNSUPERVISED LEARNING
UNSUPERVISED LEARNING
UNSUPERVISED LEARNING
UNSUPERVISED LEARNING
a.
Pertaining to theory; depending on, or confined to, theory or speculation; speculative; terminating in theory or speculation: not practical; as, theoretical learning; theoretic sciences.
n.
A beginner in learning; one who is in the rudiments of any branch of study; a person imperfectly acquainted with a subject; a novice.
n.
Instruction in school; tuition; education in an institution of learning; act of teaching.
n.
The doctrine of arts in general; such branches of learning as respect the arts.
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.
A man of learning; one versed in literature or science; a person eminent for acquirements.
n.
An institution organized and incorporated for the purpose of imparting instruction, examining students, and otherwise promoting education in the higher branches of literature, science, art, etc., empowered to confer degrees in the several arts and faculties, as in theology, law, medicine, music, etc. A university may exist without having any college connected with it, or it may consist of but one college, or it may comprise an assemblage of colleges established in any place, with professors for instructing students in the sciences and other branches of learning.
n.
One engaged in the pursuits of learning; a learned person; one versed in any branch, or in many branches, of knowledge; a person of high literary or scientific attainments; a savant.
n.
A book used in schools for learning lessons.
imp. & p. p.
of Supervise
a.
Not exhibiting learning; as, unlearned verses.
v. t.
To be without; to be destitute of, or deficient in; not to have; to lack; as, to want knowledge; to want judgment; to want learning; to want food and clothing.
prep.
As sign of the infinitive, to had originally the use of last defined, governing the infinitive as a verbal noun, and connecting it as indirect object with a preceding verb or adjective; thus, ready to go, i.e., ready unto going; good to eat, i.e., good for eating; I do my utmost to lead my life pleasantly. But it has come to be the almost constant prefix to the infinitive, even in situations where it has no prepositional meaning, as where the infinitive is direct object or subject; thus, I love to learn, i.e., I love learning; to die for one's country is noble, i.e., the dying for one's country. Where the infinitive denotes the design or purpose, good usage formerly allowed the prefixing of for to the to; as, what went ye out for see? (Matt. xi. 8).
v. t.
To train in an institution of learning; to educate at a school; to teach.
n.
The acquisition of knowledge or skill; as, the learning of languages; the learning of telegraphy.
n.
The sakti or wife of Brahma; the Hindoo goddess of learning, music, and poetry.
n.
The character and qualities of a scholar; attainments in science or literature; erudition; learning.
n.
A place for learned intercourse and instruction; an institution for learning; an educational establishment; a place for acquiring knowledge and mental training; as, the school of the prophets.
a.
Pertaining to, or suiting, a scholar, a school, or schools; scholarlike; as, scholastic manners or pride; scholastic learning.
a.
Being without; destitute; free; wanting; devoid; as, void of learning, or of common use.