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Machine-learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predict ...
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Unsupervised Learning
Unsupervised learning is a type of algorithm that learns patterns from untagged data. The hope is that through mimicry, which is an important mode of learning in people, the machine is forced to build a concise representation of its world and then generate imaginative content from it. In contrast to supervised learning where data is tagged by an expert, e.g. tagged as a "ball" or "fish", unsupervised methods exhibit self-organization that captures patterns as probability densities or a combination of neural feature preferences encoded in the machine's weights and activations. The other levels in the supervision spectrum are reinforcement learning where the machine is given only a numerical performance score as guidance, and semi-supervised learning where a small portion of the data is tagged. Neural networks Tasks vs. methods Neural network tasks are often categorized as discriminative (recognition) or generative (imagination). Often but not always, discriminative tas ...
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Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ...
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Predictive Analytics
Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions. The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detecti ...
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MNIST Database
The MNIST database (''Modified National Institute of Standards and Technology database'') is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning. It was created by "re-mixing" the samples from NIST's original datasets. The creators felt that since NIST's training dataset was taken from American Census Bureau employees, while the testing dataset was taken from American high school students, it was not well-suited for machine learning experiments. Furthermore, the black and white images from NIST were normalized to fit into a 28x28 pixel bounding box and anti-aliased, which introduced grayscale levels. The MNIST database contains 60,000 training images and 10,000 testing images. Half of the training set and half of the test set were taken from NIST's training dataset, while the other half of the training set and the other half of the test ...
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AI Hierarchy
AI is artificial intelligence, intellectual ability in machines and robots. Ai, AI or A.I. may also refer to: Animals * Ai (chimpanzee), an individual experimental subject in Japan * Ai (sloth) or the pale-throated sloth, northern Amazonian mammal species Arts, entertainment and media Works * ''Ai'' (album), a 2004 release by Seraphim * ''A.I. Artificial Intelligence'', a 2001 American film * '' A.I. Rising'', a 2018 Serbian film * '' AI: The Somnium Files'', a 2019 video game * ''American Idol'', televised singing contest * ''The American Interest'', a bimonthly magazine (2005–2020) * ''I'' (2015 film), an Indian Tamil film (initial title: ''Ai'') Other uses in arts and media * A.i. (band), a Californian rock–electroclash group * All in (poker), wagering one's entire stake * Appreciation Index, a British measure of broadcast programme approval * The Art Institutes, a chain of American art schools * Non-player character, in gaming (colloquially, ''an AI'') Business * ...
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Computing Machinery And Intelligence
"Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence. The paper, published in 1950 in ''Mind'', was the first to introduce his concept of what is now known as the Turing test to the general public. Turing's paper considers the question "Can machines think?" Turing says that since the words "think" and "machine" cannot be clearly defined we should "replace the question by another, which is closely related to it and is expressed in relatively unambiguous words." To do this, he must first find a simple and unambiguous idea to replace the word "think", second he must explain exactly which "machines" he is considering, and finally, armed with these tools, he formulates a new question, related to the first, that he believes he can answer in the affirmative. Turing's test Rather than trying to determine if a machine is thinking, Turing suggests we should ask if the machine can win a game, called the " Imitation Game" ...
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Alan Turing
Alan Mathison Turing (; 23 June 1912 – 7 June 1954) was an English mathematician, computer scientist, logician, cryptanalyst, philosopher, and theoretical biologist. Turing was highly influential in the development of theoretical computer science, providing a formalisation of the concepts of algorithm and computation with the Turing machine, which can be considered a model of a general-purpose computer. He is widely considered to be the father of theoretical computer science and artificial intelligence. Born in Maida Vale, London, Turing was raised in southern England. He graduated at King's College, Cambridge, with a degree in mathematics. Whilst he was a fellow at Cambridge, he published a proof demonstrating that some purely mathematical yes–no questions can never be answered by computation and defined a Turing machine, and went on to prove that the halting problem for Turing machines is undecidable. In 1938, he obtained his PhD from the Department of Mathemati ...
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Operational Definition
An operational definition specifies concrete, replicable procedures designed to represent a construct. In the words of American psychologist S.S. Stevens (1935), "An operation is the performance which we execute in order to make known a concept." For example, an operational definition of "fear" (the construct) often includes measurable physiologic responses that occur in response to a perceived threat. Thus, "fear" might be operationally defined as specified changes in heart rate, galvanic skin response, pupil dilation, and blood pressure. Overview An operational definition is designed to model or represent a concept or theoretical definition, also known as a construct. Scientists should describe the operations (procedures, actions, or processes) that define the concept with enough specificity such that other investigators can replicate their research. Operational definitions are also used to define system states in terms of a specific, publicly accessible process of preparation ...
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Tom M
Tom or TOM may refer to: * Tom (given name), a diminutive of Thomas or Tomás or an independent Aramaic given name (and a list of people with the name) Characters * Tom Anderson, a character in ''Beavis and Butt-Head'' * Tom Beck, a character in the 1998 American science-fiction disaster movie '' Deep Impact'' * Tom Buchanan, the main antagonist from the 1925 novel ''The Great Gatsby'' * Tom Cat, a character from the ''Tom and Jerry'' cartoons * Tom Lucitor, a character from the American animated series ''Star vs. the Forces of Evil'' * Tom Natsworthy, from the science fantasy novel ''Mortal Engines'' * Tom Nook, a character in ''Animal Crossing'' video game series * Tom Servo, a robot character from the ''Mystery Science Theater 3000'' television series * Tom Sloane, a non-adult character from the animated sitcom ''Daria'' * Talking Tom, the protagonist from the ''Talking Tom & Friends'' franchise * Tom, a character from the '' Deltora Quest'' books by Emily Rodda * Tom, a cha ...
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Neural Network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning resulting from e ...
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Time (magazine)
''Time'' (stylized in all caps) is an American news magazine based in New York City. For nearly a century, it was published Weekly newspaper, weekly, but starting in March 2020 it transitioned to every other week. It was first published in New York City on March 3, 1923, and for many years it was run by its influential co-founder, Henry Luce. A European edition (''Time Europe'', formerly known as ''Time Atlantic'') is published in London and also covers the Middle East, Africa, and, since 2003, Latin America. An Asian edition (''Time Asia'') is based in Hong Kong. The South Pacific edition, which covers Australia, New Zealand, and the Pacific Islands, is based in Sydney. Since 2018, ''Time'' has been published by Time USA, LLC, owned by Marc Benioff, who acquired it from Meredith Corporation. History ''Time'' has been based in New York City since its first issue published on March 3, 1923, by Briton Hadden and Henry Luce. It was the first weekly news magazine in the United St ...
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Goof
A goof is a mistake. The term is also used in a number of specific senses: in cinema, it is an error or oversight during production that is visible in the released version of the film. Etymology Several origins have been proposed for the word. According to Merriam-Webster, "goof" is likely a variation of "goff" in an English dialect, meaning simpleton. Some say the word may come from an identically pronounced Hebrew word meaning "body", some even say it was just a mistake that happened while typing the word "good", hence the word "goof" is also known as another word for mistake See the etymological explanation of Hessu Hopo, 'Goofy' in Finnish language. The Spanish word ''gofio'' refers to the balls of toasted flour and salt eaten by the original inhabitants of the Canary Islands. In Latin America (esp. Cuba) the word "comegofio" (lit. "gofio-eater") came to refer to anyone from the Canaries, stereotyped as primitive or stupid. Cinema In filmmaking, a ''goof'' is a mistake mad ...
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