 |
Machine Learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
Field Of Study
An academic discipline or academic field is a subdivision of knowledge that is taught and researched at the college or university level. Disciplines are defined (in part) and recognized by the academic journals in which research is published, and the learned society, learned societies and academic departments or faculties within colleges and universities to which their practitioners belong. Academic disciplines are conventionally divided into the humanities (including philosophy, Linguistics, language, art and cultural studies), the scientific disciplines (such as physics, chemistry, and biology); and the formal sciences like mathematics and computer science. The social sciences are sometimes considered a fourth category. It is also known as a ''field of study'', ''field of inquiry'', ''research field'' and ''branch of knowledge''. The different terms are used in different countries and fields. Individuals associated with academic disciplines are commonly referred to as ''expert ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
|
Predictive Analytics
Predictive analytics encompasses a variety of Statistics, statistical techniques from data mining, Predictive modelling, 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 Pattern detection, 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
 |
Nerve Cells
A neuron (American English), neurone (British English), or nerve cell, is an excitable cell that fires electric signals called action potentials across a neural network in the nervous system. They are located in the nervous system and help to receive and conduct impulses. Neurons communicate with other cells via synapses, which are specialized connections that commonly use minute amounts of chemical neurotransmitters to pass the electric signal from the presynaptic neuron to the target cell through the synaptic gap. Neurons are the main components of nervous tissue in all animals except sponges and placozoans. Plants and fungi do not have nerve cells. Molecular evidence suggests that the ability to generate electric signals first appeared in evolution some 700 to 800 million years ago, during the Tonian period. Predecessors of neurons were the peptidergic secretory cells. They eventually gained new gene modules which enabled cells to create post-synaptic scaffolds and ion ch ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
Hebbian Theory
Hebbian theory is a neuropsychological theory claiming that an increase in synaptic efficacy arises from a presynaptic cell's repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation of neurons during the learning process. Hebbian theory was introduced by Donald Hebb in his 1949 book '' The Organization of Behavior.'' The theory is also called Hebb's rule, Hebb's postulate, and cell assembly theory. Hebb states it as follows: Let us assume that the persistence or repetition of a reverberatory activity (or "trace") tends to induce lasting cellular changes that add to its stability. ... When an axon of cell ''A'' is near enough to excite a cell ''B'' and repeatedly or persistently takes part in firing it, some growth process or metabolic change takes place in one or both cells such that ''A''’s efficiency, as one of the cells firing ''B'', is increased. The theory is often summarized as "Neurons that fire togethe ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
|
Organization Of Behavior
''Organization of Behavior'' is a 1949 book by the psychologist Donald O. Hebb. One of the main takeaways was that it proposed a theory about learning based on conjunctures on neural networks A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either Cell (biology), biological cells or signal pathways. While individual neurons are simple, many of them together in a netwo ... and synapses being able to strengthen or weaken over time. Reception The author Richard Webster identifies ''Organization of Behavior'' as the most influential outline of Hebb's postulate. According to Webster, the hypothesis has classic status within science and is supported by recent research. References Bibliography ;Books * 1949 non-fiction books Books by Donald O. Hebb English-language non-fiction books Neuroscience books {{Nonfiction-book-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
|
Donald O
Donald is a Scottish masculine given name. It is derived from the Gaelic name ''Dòmhnall''.. This comes from the Proto-Celtic *''Dumno-ualos'' ("world-ruler" or "world-wielder"). The final -''d'' in ''Donald'' is partly derived from a misinterpretation of the Gaelic pronunciation by English speakers. A short form of Donald is Don, and pet forms of Donald include Donnie and Donny. The feminine given name Donella is derived from Donald. ''Donald'' has cognates in other Celtic languages: Modern Irish ''Dónal'' (anglicised as ''Donal'' and ''Donall'');. Scottish Gaelic ''Dòmhnall'', ''Domhnull'' and ''Dòmhnull''; Welsh '' Dyfnwal'' and Cumbric ''Dumnagual''. Although the feminine given name '' Donna'' is sometimes used as a feminine form of ''Donald'', the names are not etymologically related. Variations Kings and noblemen Domnall or Domhnall is the name of many ancient and medieval Gaelic kings and noblemen: * Dyfnwal Moelmud (Dunvallo Molmutius), legendary kin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
 |
Canadians
Canadians () are people identified with the country of Canada. This connection may be residential, legal, historical or cultural. For most Canadians, many (or all) of these connections exist and are collectively the source of their being ''Canadian''. Canada is a multilingual and multicultural society home to people of groups of many different ethnic, religious, and national origins, with the majority of the population made up of Old World immigrants and their descendants. Following the initial period of French and then the much larger British colonization, different waves (or peaks) of immigration and settlement of non-indigenous peoples took place over the course of nearly two centuries and continue today. Elements of Indigenous, French, British, and more recent immigrant customs, languages, and religions have combined to form the culture of Canada, and thus a Canadian identity and Canadian values. Canada has also been strongly influenced by its linguistic, geograph ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
 |
Computer Program
A computer program is a sequence or set of instructions in a programming language for a computer to Execution (computing), execute. It is one component of software, which also includes software documentation, documentation and other intangible components. A ''computer program'' in its human-readable form is called source code. Source code needs another computer program to Execution (computing), execute because computers can only execute their native machine instructions. Therefore, source code may be Translator (computing), translated to machine instructions using a compiler written for the language. (Assembly language programs are translated using an Assembler (computing), assembler.) The resulting file is called an executable. Alternatively, source code may execute within an interpreter (computing), interpreter written for the language. If the executable is requested for execution, then the operating system Loader (computing), loads it into Random-access memory, memory and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
 |
Computer Gaming
A video game or computer game is an electronic game that involves interaction with a user interface or input device (such as a joystick, controller, keyboard, or motion sensing device) to generate visual feedback from a display device, most commonly shown in a video format on a television set, computer monitor, flat-panel display or touchscreen on handheld devices, or a virtual reality headset. Most modern video games are audiovisual, with audio complement delivered through speakers or headphones, and sometimes also with other types of sensory feedback (e.g., haptic technology that provides tactile sensations). Some video games also allow microphone and webcam inputs for in-game chatting and livestreaming. Video games are typically categorized according to their hardware platform, which traditionally includes arcade video games, console games, and computer games (which includes LAN games, online games, and browser games). More recently, the video game industry has expan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
Probably Approximately Correct Learning
In computational learning theory, probably approximately correct (PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant.L. Valiant. A theory of the learnable.' Communications of the ACM, 27, 1984. In this framework, the learner receives samples and must select a generalization function (called the ''hypothesis'') from a certain class of possible functions. The goal is that, with high probability (the "probably" part), the selected function will have low generalization error (the "approximately correct" part). The learner must be able to learn the concept given any arbitrary approximation ratio, probability of success, or distribution of the samples. The model was later extended to treat noise (misclassified samples). An important innovation of the PAC framework is the introduction of computational complexity theory concepts to machine learning. In particular, the learner is expected to find efficient functions (t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
|
 |
Unsupervised Learning
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks in the spectrum of supervisions include weak- or semi-supervision, where a small portion of the data is tagged, and self-supervision. Some researchers consider self-supervised learning a form of unsupervised learning. Conceptually, unsupervised learning divides into the aspects of data, training, algorithm, and downstream applications. Typically, the dataset is harvested cheaply "in the wild", such as massive text corpus obtained by web crawling, with only minor filtering (such as Common Crawl). This compares favorably to supervised learning, where the dataset (such as the ImageNet1000) is typically constructed manually, which is much more expensive. There were algorithms designed specifically for unsupervised learning, such as clustering algorithms like k-means, dimensionality reduction techniques l ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
 |
Exploratory Data Analysis
In statistics, exploratory data analysis (EDA) is an approach of data analysis, analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell beyond the formal modeling and thereby contrasts with traditional hypothesis testing, in which a model is supposed to be selected before the data is seen. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments. EDA is different from Data analysis#Initial data analysis, initial data analysis (IDA), which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed. EDA encompasses IDA. Overview Tukey defined data analysi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |