359.866 hasil untuk machine learning
Menampilkan 961–980 · 1,90 detik · RSS
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Artikel Jurnal Teks lengkap
Machine Learning of Spatial Data
Properties of spatially explicit data are often ignored or inadequately handled in machine learning for spatial domains of application. At the same time, resources that would identify these properties and investigate their influence and methods to handle them in machine learning applications are…
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Machine learning in materials science
…due to its low computational cost and short development cycle, machine learning is coupled with powerful data processing and high prediction performance and is being widely used in material detection, material analysis, and material design. In this article, we discuss the basic operational…
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Dysgraphia detection through machine learning
…early intervention for those who need it. In this paper, we employed a machine learning approach to identify handwriting deteriorated by dysgraphia. To achieve this goal, we collected a new handwriting dataset consisting of several handwriting tasks and extracted a broad range of features to…
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Artikel Jurnal Teks lengkap
Machine Learning in Big Data
Machine learning is an artificial intelligence method of discovering knowledge for making intelligent decisions. Big Data has great impacts on scientific discoveries and value creation. This paper introduces methods in machine learning, main technologies in Big Data, and some applications of…
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Machine Learning–Driven Language Assessment
…can be valid, reliable, and secure. Our approach is the first to use machine learning and natural language processing to induce proficiency scales based on a given standard, and then use linguistic models to estimate item difficulty directly for computer-adaptive testing. This alleviates the need…
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Machine learning in polymer informatics
…has brought challenges to their development. Thanks to the integration of machine learning algorithms and large data resources, the data‐driven methods have opened up a new road for the development of polymer science and engineering. The emerging polymer informatics attempts to accelerate the…
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Machine-learning reprogrammable metasurface imager
Conventional imagers require time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing. Here, the authors demonstrate a real-time digital-metasurface imager that can be trained in-situ to show high accuracy image coding and recognition for various image sets.
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Artikel Jurnal Teks lengkap
Machine learning for algorithmic trading
The purpose of the study is to confirm the feasibility of using machine learning methods to predict the behavior of the foreign exchange market. The article examines the theoretical and practical aspects of the implementation of artificial neural networks in the process of Internet trading. We…
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Machine learning and quantum devices
These brief lecture notes cover the basics of neural networks and deep learning as well as their applications in the quantum domain, for physicists without prior knowledge. In the first part, we describe training using backpropagation, image classification, convolutional networks and autoencoders…
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Cyberbullying Detection using Machine Learning
It is an age of the Internet and electronic media, and social media platforms are one of the most frequently used communication medium nowadays. But some people use these sites for malicious purpose and among those negative aspects "Cyberbullying" is prevalent. Cyberbullying is a form of bullying…
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Artikel Jurnal Teks lengkap
Machine Learning with ROOT/TMVA
ROOT provides, through TMVA, machine learning tools for data analysis at HEP experiments and beyond. We present recently included features in TMVA and the strategy for future developments in the diversified machine learning landscape. Focus is put on fast machine learning inference, which enables…
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Artikel Jurnal
Distributed machine learning for IoT
In the modern world, big data is used in machine learning, which is quite difficult to process on a single computer, so various methods for parallel processing of such data are being developed. But what about microcontrollers? In a cloud system, microcontrollers are often found, thanks to which…
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Artikel Jurnal
Using Machine Learning in Forestry
…in the number of academic studies in which modern approaches such as machine learning and recently emerged automatic machine learning (AutoML) are integrated into decision-making processes in forestry. This study aims to increase further the comprehensibility of machine learning algorithms in the…
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Machine learning for quantum matter
…systems have turned their attention to the algorithms underlying modern machine learning with an eye on making progress in their fields. Here we provide a short review on the recent development and adaptation of machine learning ideas for the purpose advancing research in quantum matter, including…
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Jet charge and machine learning
Abstract Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or W boson identification or for quark/gluon…
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Machine learning line bundle connections
We study the use of machine learning for finding numerical hermitian Yang–Mills connections on line bundles over Calabi–Yau manifolds. Defining an appropriate loss function and focusing on the examples of an elliptic curve, a K3 surface and a quintic threefold, we show that neural networks can be…
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Machine Learning in E-Commerce
…functionality and advanced implementation based on the integration of machine learning algorithms. The adequacy and advantages / disadvantages of different methods, such as general recommendation systems and content-based recommendations, were analyzed and presented. This type of implementation is…
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