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[SOURCE: https://en.wikipedia.org/wiki/Noam_Chomsky] | [TOKENS: 13932] |
Contents Noam Chomsky Avram Noam Chomsky[a] (born December 7, 1928) is an American professor and public intellectual known for his work in linguistics, political activism, and social criticism. Sometimes called "the father of modern linguistics",[b] Chomsky is also a major figure in analytic philosophy and one of the f... |
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[SOURCE: https://en.wikipedia.org/wiki/Word_n-gram_language_model#Skip-gram_language_model] | [TOKENS: 2918] |
Contents Word n-gram language model A word n-gram language model is a statistical model of language which calculates the probability of the next word in a sequence from a fixed size window of previous words. If one previous word is considered, it is a bigram model; if two words, a trigram model; if n − 1 words, an n-gr... |
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[SOURCE: https://en.wikipedia.org/wiki/Regularization_(mathematics)] | [TOKENS: 6846] |
Contents Regularization (mathematics) In mathematics, statistics, finance, and computer science, particularly in machine learning and inverse problems, regularization is a process that converts the answer to a problem to a simpler one. It is often used in solving ill-posed problems or to prevent overfitting. Although r... |
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[SOURCE: https://en.wikipedia.org/wiki/Language_model#cite_note-Word_n-gram_language_model_compositionality-17] | [TOKENS: 1793] |
Contents Language model A language model is a computational model that predicts sequences in natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimiz... |
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[SOURCE: https://en.wikipedia.org/wiki/Curse_of_dimensionality] | [TOKENS: 3571] |
Contents Curse of dimensionality The curse of dimensionality refers to various phenomena that arise when analyzing and organizing data in high-dimensional spaces that do not occur in low-dimensional settings such as the three-dimensional physical space of everyday experience. The expression was coined by Richard E. Bel... |
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[SOURCE: https://en.wikipedia.org/wiki/Language_model#cite_note-Word_n-gram_language_model_mikolov-16] | [TOKENS: 1793] |
Contents Language model A language model is a computational model that predicts sequences in natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimiz... |
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[SOURCE: https://en.wikipedia.org/wiki/Word_embedding] | [TOKENS: 1911] |
Contents Word embedding In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be s... |
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[SOURCE: https://en.wikipedia.org/wiki/Claude_Shannon] | [TOKENS: 5613] |
Contents Claude Shannon Claude Elwood Shannon (April 30, 1916 – February 24, 2001) was an American polymath who was a mathematician, electrical engineer, computer scientist, cryptographer and inventor known as the "father of information theory" and the man who laid the foundations of the Information Age. Shannon was th... |
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[SOURCE: https://en.wikipedia.org/wiki/Meta-learning_(computer_science)] | [TOKENS: 941] |
Contents Meta-learning (computer science) Meta-learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automati... |
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[SOURCE: https://en.wikipedia.org/wiki/Rule-based_machine_learning] | [TOKENS: 365] |
Contents Rule-based machine learning Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. The defining characteristic of a rule-based machine learner is the identification and utiliza... |
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[SOURCE: https://en.wikipedia.org/wiki/Online_machine_learning] | [TOKENS: 7055] |
Contents Online 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 the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning... |
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[SOURCE: https://en.wikipedia.org/wiki/Quantum_machine_learning] | [TOKENS: 6226] |
Contents Quantum machine learning Quantum machine learning (QML) is the study of quantum algorithms for machine learning. It often refers to quantum algorithms for machine learning tasks which analyze classical data, sometimes called quantum-enhanced machine learning. QML algorithms use qubits and quantum operations to... |
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[SOURCE: https://en.wikipedia.org/wiki/Data_cleaning] | [TOKENS: 1021] |
Contents Data cleansing Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the af... |
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[SOURCE: https://en.wikipedia.org/wiki/Neuromorphic_engineering] | [TOKENS: 908] |
Contents Neuromorphic computing Neuromorphic computing is a computing approach inspired by the human brain's structure and function. It uses artificial neurons to perform computations, mimicking neural systems for tasks such as perception, motor control, and multisensory integration. These systems, implemented in analo... |
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[SOURCE: https://en.wikipedia.org/wiki/Structured_prediction] | [TOKENS: 589] |
Contents Structured prediction Structured prediction or structured output learning is an umbrella term for supervised machine learning techniques that involves predicting structured objects, rather than discrete or real values. Similar to commonly used supervised learning techniques, structured prediction models are ty... |
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[SOURCE: https://en.wikipedia.org/wiki/Reinforcement_learning] | [TOKENS: 6752] |
Contents Reinforcement learning In machine learning and optimal control, reinforcement learning (RL) is concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside superv... |
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[SOURCE: https://en.wikipedia.org/wiki/Feature_engineering] | [TOKENS: 1044] |
Contents Feature engineering Feature engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set of inputs. Each input comprises several attributes, known as features. By providing models with relevant information, feature engineering s... |
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[SOURCE: https://en.wikipedia.org/wiki/Feature_learning] | [TOKENS: 3879] |
Contents Feature learning In machine learning (ML), feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both lea... |
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[SOURCE: https://en.wikipedia.org/wiki/Multimodal_learning] | [TOKENS: 1357] |
Contents Multimodal learning 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, or video. This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual ... |
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[SOURCE: https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm] | [TOKENS: 4618] |
Contents k-nearest neighbors algorithm In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric supervised learning method. It was first developed by Evelyn Fix and Joseph Hodges in 1951, and later expanded by Thomas Cover. Most often, it is used for classification, as a k-NN classifier, the output o... |
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[SOURCE: https://he.wikipedia.org/wiki/ירוק] | [TOKENS: 1120] |
תוכן עניינים ירוק ירוק הוא צבע המתקבל על ידי אור בתחום אורכי גל מקורב של 520–570 ננומטר (תדירות מקורבת בין 525 ל-575 טרה-הרץ) בספקטרום הנראה לעין. רגישותם של התאים קולטי האור לאחר הסתגלות לחשיכה (העקומה הסקוטופית) היא מרבית באורך גל של 507 ננומטר, בקירוב, המתאים לצבע כחול-ירוק, בעוד שלאחר הסתגלות לתנאי אור (העקומה הפוט... |
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[SOURCE: https://en.wikipedia.org/wiki/Bootstrap_aggregating] | [TOKENS: 2062] |
Contents Bootstrap aggregating Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms. It also reduces variance and overfitting. Although it... |
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[SOURCE: https://en.wikipedia.org/wiki/Fuzzy_clustering] | [TOKENS: 1968] |
Contents Fuzzy clustering Fuzzy clustering (also referred to as soft clustering or soft k-means) is a form of clustering in which each data point can belong to more than one cluster. Clustering or cluster analysis involves assigning data points to clusters such that items in the same cluster are as similar as possible,... |
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[SOURCE: https://en.wikipedia.org/wiki/Perceptron] | [TOKENS: 6506] |
Contents Perceptron In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers. A binary classifier is a function that can decide whether or not an input, represented by a vector of numbers, belongs to some specific class. It is a type of linear classifier, i.e. a classification a... |
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[SOURCE: https://en.wikipedia.org/wiki/Artificial_neural_network] | [TOKENS: 9727] |
Contents Neural network (machine learning) In machine learning, a neural network (NN) or neural net, also called an artificial neural network (ANN), is a computational model inspired by the structure and functions of biological neural networks. A neural network consists of connected units or nodes called artificial neu... |
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