3.327 hasil untuk machine learning
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Artikel Jurnal Teks lengkap
Machine learning in manufacturing and industry 4.0 applications
The machine learning (ML) field has deeply impacted the manufacturing industry in the context of the Industry 4.0 paradigm. The industry 4.0 paradigm encourages the usage of smart sensors, devices, and machines, to enable smart factories that continuously collect data pertaining to production. ML…
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Membership Inference Attacks on Machine Learning: A Survey
Machine learning (ML) models have been widely applied to various applications, including image classification, text generation, audio recognition, and graph data analysis. However, recent studies have shown that ML models are vulnerable to membership inference attacks (MIAs), which aim to infer…
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Machine learning for perovskite materials design and discovery
Abstract The development of materials is one of the driving forces to accelerate modern scientific progress and technological innovation. Machine learning (ML) technology is rapidly developed in many fields and opening blueprints for the discovery and rational design of materials. In this review…
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Machine-Learning-Based Disease Diagnosis: A Comprehensive Review
…in developing the early diagnosis tool and effective treatment. Machine learning (ML), an area of artificial intelligence (AI), enables researchers, physicians, and patients to solve some of these issues. Based on relevant research, this review explains how machine learning (ML) is being used to…
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Effective Heart Disease Prediction Using Machine Learning Techniques
…which helps cardiologists provide proper treatment to the patient. Machine learning applications in the medical niche have increased as they can recognize patterns from data. Using machine learning to classify cardiovascular disease occurrence can help diagnosticians reduce misdiagnosis. This…
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Buku
Multivariate Statistical Machine Learning Methods for Genomic Prediction
This open access book presents the state of the art genome base prediction models and statistical learning tools
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How is machine learning useful for macroeconomic forecasting?
Summary We move beyond Is Machine Learning Useful for Macroeconomic Forecasting? by adding the how . The current forecasting literature has focused on matching specific variables and horizons with a particularly successful algorithm. To the contrary, we study the usefulness of the underlying…
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Machine learning for antimicrobial peptide identification and design
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Artikel Jurnal
Machine Learning for Social Science: An Agnostic Approach
Social scientists are now in an era of data abundance, and machine learning tools are increasingly used to extract meaning from data sets both massive and small. We explain how the inclusion of machine learning in the social sciences requires us to rethink not only applications of machine learning…
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Testing machine learning based systems: a systematic mapping
Abstract Context: A Machine Learning based System (MLS) is a software system including one or more components that learn how to perform a task from a given data set. The increasing adoption of MLSs in safety critical domains such as autonomous driving, healthcare, and finance has fostered much…
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Machine Learning for Microcontroller-Class Hardware: A Review
The advancements in machine learning opened a new opportunity to bring intelligence to the low-end Internet-of-Things nodes such as microcontrollers. Conventional machine learning deployment has high memory and compute footprint hindering their direct deployment on ultra resource-constrained…
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Recent Progresses in Machine Learning Assisted Raman Spectroscopy
…an area of intensifying focus for research. It has been demonstrated that machine learning techniques can more efficiently extract valuable information from spectral data, creating unprecedented opportunities for analytical science. This paper outlines traditional and more recently developed…
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Two-step machine learning enables optimized nanoparticle synthesis
…and time-consuming. In this study, we present a two-step framework for a machine learning-driven high-throughput microfluidic platform to rapidly produce silver nanoparticles with the desired absorbance spectrum. Combining a Gaussian process-based Bayesian optimization (BO) with a deep neural…
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Artikel Jurnal
Algorithmic bias in machine learning-based marketing models
This article introduces algorithmic bias in machine learning (ML) based marketing models. Although the dramatic growth of algorithmic decision making continues to gain momentum in marketing, research in this stream is still inadequate despite the devastating, asymmetric and oppressive impacts of…
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Artikel Jurnal
Review of machine learning methods in soft robotics
…limitations, recent studies have applied various approaches based on machine learning. This paper presents existing machine learning techniques in the soft robotic fields and categorizes the implementation of machine learning approaches in different soft robotic applications, which include soft…
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Prediction of EV Charging Behavior Using Machine Learning
…to manage the growing public charging demand. Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. Researchers have focused on using historical charging data for predictions of behavior such as departure time and energy needs…
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Using machine learning for healthcare challenges and opportunities
Machine learning (ML) and its applications in healthcare have gained a lot of attention. When enhanced computational power is combined with big data, there is an opportunity to use ML algorithms to improve health care. Supervised learning is the type of ML that can be implemented to predict labeled…
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