Machine learning (ML)
Machine Learning for drugs prescription
... Recently, Machine Learning (ML) has gained a lot of recognition and people are trying to use it to solve some of their problems. Researchers have developed systems, based on classification models, in order ...
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Assessing irace for automated machine learning
... Convenient as these packages may be for the application of ML by non-experts, they still leave most of the algorithm engineering process up to the user: (i) if and how to preprocess the data; (ii) how to extract, reduce, ...
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Automatic Habitat Mapping using Machine Learning
... With this work we can state that CNNs are not a reliable solution to perform image classification with low amount of data samples, although they tend to scale very quickly when given a significant amount of images. Also, ...
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Unveiling phase transitions with machine learning
... a machine learning frame- work to analyze the phase diagram and phase transitions of quantum .../transfer learning and showed how transfer learning becomes possible: by train- ing the ...
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Machine learning in supply chain management
... of machine learning (ML) under the guise of artificial intelligence (Siau et ...with learning systems, without knowing it (Harvard Business Manager, ...
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March madness prediction using machine learning techniques
... Machine Learning is the subgroup of computer science and artificial intelligence that provides computers the ability to learn, without being explicitly programmed, and perform specific ...Turing ...
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Machine learning: O Uso da Inteligência Artificial na Medicina/ Machine learning: The Use of Artificial Intelligence in Medicine
... o Machine learning (ML- aprendizado de máquina, área da inteligência artificial), fornece um caminho para melhorar a precisão e a confiabilidade das modalidades diagnósticas e tem o potencial de contribuir ...
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Forecasting Stock Markets Using Machine Learning
... Some relevant articles about using ML techniques to predict the stock markets are listed here.Atsalakis & Valavanis (2009) presents a survey on neural and neuro-fuzzy techniques to forecast stock markets. It is shown ...
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Adversarial machine learning: denial of services recognition
... a machine learning algorithm that consists of applying the Bayes the- orem in order to find a distribution of conditional probabilities among class labels, with the assumption of independence between ...
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Predicting start-up success with machine learning
... In machine learning, the coefficients of the logistic regression algorithm must be estimated from the training data, with LR this is done using maximum-likelihood estimation (Jason Brownlee, ...
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Aplicação de técnicas de Machine Learning na combinação de pesquisas eleitorais
... The Brazilian electoral polls are made, mostly, from a non-probabilistic sample plan by quotas. Thus, there is an accumulation of uncertainties regarding the estimates obtained, since there is no way to guarantee that ...
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Sono ao Volante - Machine Learning para Previsão e Deteção de Sonolência
... As medidas comportamentais são focadas na capacidade de concentração do condutor, deteta- das principalmente por técnicas de processamento de imagem [ 43 ]. A fonte de informação visual pode incluir a expressão facial, ...
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Machine learning methods to predict wind intensity
... Genetic Algorithms are Machine Learning algo- rithms that use the metaphor of Evolution of Species and Natural Selection law in optimization problems. As GAs use special encoding schemes for the param- ...
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Previsão de resultado de jogos da NBA com algoritmos de machine learning
... Os algoritmos devem ser capazes de analisar conjuntos de dados massivos e aprender com eles. Quando os algoritmos são treinados com dados onde o resultado desejado é conhecido, temos uma aprendizagem supervisionada, ...
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Servindo modelos de machine learning com uma arquitetura baseada em serverless
... Ambiente de teste. Como foi mostrado no capítulo de trabalhos relacionados, outros trabalhos da área de Machine Learning realizaram os experimentos dos seus testes em clusters de computadores com pelo menos ...
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Predspot: predicting crime hotspots with machine learning
... Smart cities are increasingly adopting data infrastructure and analysis to improve the decision-making process for public safety issues. Although traditional hotspot policing methods have shown benefits in reducing ...
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Deteção de fraude em telecomunicações através de machine learning
... Specifically, this dissertation focused on an operator’s database, with information about calls received in a gateway, aiming to identify frauds such as bypass and wangiri. Firstly, an exploratory analysis based on ...
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Machine Learning em Química Orgânica
... Figura 1 – Visão geral da área de Inteligência Artificial do ponto de vista das aplicações (à esquerda) e dos métodos utilizados (à direita). ............................... 6 Figura 2 – Os algoritmos de Machine ...
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Information retrieval using machine learning for database curation
... the machine learning models ...Vector Machine) were evaluated to predict an article’s relevance based on its title, abstract or ...Vector Machine algorithm using the abstracts’ set, achieving ...
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Machine learning no processo de risco de crédito das instituições bancárias
... o machine learning que permite que softwares e máquinas identifiquem automaticamente o comportamento ideal dentro de um quadro preciso, de modo a maximizar seu desempenho (Giryes & Elad, ...
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