204.674 hasil untuk machine learning
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Artikel Jurnal
Machine Learning Based Chat Analysis
The BYU library implemented a Machine Learning-based tool to perform various text analysis tasks on transcripts of chat-based interactions between patrons and librarians. These text analysis tasks included estimating patron satisfaction and classifying queries into various categories such as…
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Artikel Jurnal
Heart Disease UCI Machine Learning
Dataset yang digunakan bersumber dari https://archive.ics.uci.edu/ml/datasets/heart+disease
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Artikel Jurnal Teks lengkap
Machine learning robot polishing cell
…and a force sensor for measuring the polishing pressure. By means of a machine learning system, predictions of tool wear and the related surface quality shall be made. The aim is the detection of the critical influence factors during the polishing process and to have a predictive maintenance system…
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Artikel Jurnal
Machine learning for chemical discovery
…molecules are becoming increasingly available. The development of novel machine learning tools to obtain chemical knowledge from these datasets has the potential to revolutionize the process of chemical discovery. Here, I comment on recent breakthroughs in this emerging field and discuss the…
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Artikel Jurnal
Exploring supersymmetry with machine learning
…task. In this paper, we propose a self-exploration method, named Machine Learning Scan (MLS), to achieve an efficient test of models. As a proof-of-concept, we apply MLS to investigate the subspace of MSSM and CMSSM and find that such a method can reduce the computational cost and may be helpful…
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Artikel Jurnal
Machine Learning: Quantum vs Classical
Encouraged by growing computing power and algorithmic development, machine learning technologies have become powerful tools for a wide variety of application areas, spanning from agriculture to chemistry and natural language processing. The use of quantum systems to process classical data using…
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Machine Learning-Enhanced Pairs Trading
…one-minute granularity over a full year, we apply various statistical and machine learning algorithms, including Bidirectional Long Short-Term Memory (BiLSTM) with attention, Transformers, N-BEATS, N-HiTS, Convolutional Neural Networks (CNNs), and Temporal Convolutional Networks (TCNs) to predict…
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Machine Learning for Quantum Metrology
…number of probes is employed. Here, we discuss an asymptotically optimal, machine learning based, adaptive single-photon phase estimation protocol that allows us to reach the standard quantum limit when a very limited number of photons is employed.
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Machine Learning and Antibiotic Management
Machine learning and cluster analysis applied to the clinical setting of an intensive care unit can be a valuable aid for clinical management, especially with the increasing complexity of clinical monitoring. Providing a method to measure clinical experience, a proxy for that automatic gestalt…
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Artikel Jurnal
Radiometer calibration using machine learning
…reference source to mitigate errors by comparison. Recent advances in Machine Learning (ML) offer promising alternatives. Neural networks, which are trained using known signal sources, provide a powerful means to model and calibrate complex systems where traditional analytical approaches struggle…
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Artikel Jurnal
LLR estimation using machine learning
…for high-order modulations and its estimation using supervised machine learning, without requiring prior knowledge of the noise distribution model. To this end, we propose two approaches to approximate the LLR values using supervised machine learning, for high-order modulated symbols. The first…
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Differentiable programming in machine learning
…implementation methods. In the context of issues encountered in machine learning and deep learning, the forward mode is deemed more suitable as it efficiently differentiates functions with numerous inputs compared to outputs. Given Python's pivotal role in the ML landscape, the paper elaborates on…
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Artikel Jurnal
Machine Learning Potential for Serpentines
…samples and the large number of atoms in the unit cell. We developed a machine learning (ML) potential for serpentine minerals based on density functional theory calculation with the r2SCAN meta‐GGA functional for molecular dynamics simulation. We illustrate the success of this ML potential model…
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Artikel Jurnal Teks lengkap
Earthquake prognosis using machine learning
…well as the environment. In this project, the successful application of machine learning techniques have been used for different elements of research which would be possible to use to make a more accurate short-term prognosis of upcoming earthquakes. Random Forest Classifier is the algorithm used…
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