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359.866 hasil untuk machine learning

Menampilkan 201–220 · 1,75 detik · RSS

  1. Buku Teks lengkap

    Application of Machine Learning

    Zhang, Yagang

    IntechOpen · 2010 · Inggris · DOAB

    The goal of this book is to present the latest applications of machine learning, which mainly include: speech recognition, traffic and fault classification, surface quality prediction in laser machining, network security and bioinformatics, enterprise credit risk evaluation, and so on. This book…

  2. Buku

    Machine Learning in Tribology

    Tremmel, Stephan; Marian, Max

    MDPI - Multidisciplinary Digital Publishing Institute · 2022 · Inggris · DOAB

    …this sound and data-rich foundation, advanced data handling, analysis and learning methods can be developed and employed to expand existing knowledge. Therefore, modern machine learning (ML) or artificial intelligence (AI) methods provide opportunities to explore the complex processes in…

  3. Buku

    Applied Machine Learning Ⅱ

    Dudek, Grzegorz

    MDPI - Multidisciplinary Digital Publishing Institute · 2024 · Inggris · DOAB

    This reprint focuses on applications of machine learning models in a diverse range of fields and problems. It reports substantive results on a wide range of learning methods; discusses the conceptualization of problems, data representation, feature engineering, and machine learning models…

  4. Buku Teks lengkap

    Data Mining and Machine Learning in Building Energy Analysis

    Magoules, F.; Zhao, H.-X.

    Wiley-ISTE, London, UK · 2016 · Inggris · HAL

    …single and multiple buildings. Based on these datasets, Support Vector Machine (SVM) models are trained and tested to do the prediction. Suitable for novice, intermediate, and advanced readers, this is a vital resource for building designers, engineers, and students.

  5. Buku Teks lengkap

    Reproducing kernel methods for machine learning, PDEs, and statistics

    Lefloch, Philippe; Mercier, Jean-Marc; Miryusupov, Shohruh

    SIAM · 2025 · Inggris · HAL

    …analogues of differential operators and variational tools that connect learning with PDE-style modeling. Part II turns to practice across four domains. In machine learning, we treat supervised and unsupervised tasks, then develop RKHS-based generative modeling, contrasting density and projection…

  6. Artikel Jurnal Teks lengkap

    Evolving Privacy Protections for Emerging Machine Learning Data Under Carpenter v. United States

    Nicolella, Emily

    FIU Law Review · 2023 · Inggris · Law Review Commons

    …that is constantly being collected by tech companies through the use of machine learning algorithms. Companies like Facebook and Google use machine learning to specifically tailor each user’s experience to their individual preferences. To do so, machine learning algorithms constantly collect…

  7. Artikel Jurnal Teks lengkap

    Explaining Compassionate Release: A Machine Learning Study of Sentencing Modifications & Judicial Decision Making

    Alderman, Max; Barfar, Arash; Edberg, Dana

    Loyola of Los Angeles Law Review · 2026 · Inggris · Law Review Commons

    …compassionate-release decision making. Until now. Using cutting-edge machine-learning tools in a mixed- methods research design, we built two algorithmic models to analyze the impact of 149 variables on 553 compassionate-release decisions. Our first, “all-inclusive” model determined with…

  8. Artikel Jurnal Teks lengkap

    Machine-learning media bias

    Samantha D’Alonzo; Max Tegmark

    PLOS ONE, Vol. 17 No. 8 · 2022 · Inggris · PLOS Scopus

    We present an automated method for measuring media bias. Inferring which newspaper published a given article, based only on the frequencies with which it uses different phrases, leads to a conditional probability distribution whose analysis lets us automatically map newspapers and phrases into a…

  9. Artikel Jurnal Teks lengkap

    Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning

    Marmolejo-Ramos, Fernando; Ospina, Raydonal; García-Ceja, Enrique dkk.

    J Stat Theory Appl · 2022 · Inggris · PubMed Central

    In The hitchhiker’s guide to responsible machine learning, Biecek, Kozak, and Zawada (here BKZ) provide an illustrated and engaging step-by-step guide on how to perform a machine learning (ML) analysis such that the algorithms, the software, and the entire process is interpretable and transparent…

  10. Artikel Jurnal Teks lengkap

    Can Machine Learning Provide Understanding? How Cosmologists Use Machine Learning to Understand Observations of the Universe

    Meskhidze, Helen

    Erkenntnis · 2021 · Inggris · PubMed Central

    …these observations has become impractical. Simulators have thus turned to machine learning (ML) algorithms instead. Though ML decreases computational expense, one might be worried about the use of ML for scientific investigations: How can algorithms that have repeatedly been described as…

  11. Artikel Jurnal

    Conservation machine learning

    Moshe Sipper; Jason H. Moore

    BioData Mining, Vol. 13 No. 1 · 2020 · Inggris · DOAJ Scopus

  12. Artikel Jurnal

    Qudit machine learning

    Sebastián Roca-Jerat; Juan Román-Roche; David Zueco

    Machine Learning: Science and Technology, Vol. 5 No. 1 · 2024 · Inggris · DOAJ Scopus

    We present a comprehensive investigation into the learning capabilities of a simple d -level system (qudit). Our study is specialized for classification tasks using real-world databases, specifically the Iris, breast cancer, and MNIST datasets. We explore various learning models in the metric…

  13. Artikel Jurnal Teks lengkap

    Explainable Machine Learning

    Jochen Garcke; Ribana Roscher

    Machine Learning and Knowledge Extraction, Vol. 5 No. 1 · 2023 · Inggris · DOAJ Scopus

    Machine learning methods are widely used in commercial applications and in many scientific areas [...]

  14. Artikel Jurnal Teks lengkap

    Precision Machine Learning

    Eric J. Michaud; Ziming Liu; Max Tegmark

    Entropy, Vol. 25 No. 1 · 2023 · Inggris · DOAJ Scopus

    We explore unique considerations involved in fitting machine learning (ML) models to data with very high precision, as is often required for science applications. We empirically compare various function approximation methods and study how they scale with increasing parameters and data. We find that…

  15. Artikel Jurnal

    Review and comparative analysis of machine learning libraries for machine learning

    Migran N. Gevorkyan; Anastasia V. Demidova; Tatiana S. Demidova dkk.

    Discrete and Continuous Models and Applied Computational Science, Vol. 27 No. 4 · 2019 · Inggris · DOAJ Scopus

    The article is an overview. We carry out the comparison of actual machine learning libraries that can be used the neural networks development. The first part of the article gives a brief description of TensorFlow, PyTorch, Theano, Keras, SciKit Learn libraries, SciPy library stack. An overview of…

  16. Artikel Jurnal Teks lengkap

    Machine learning on normalized protein sequences

    Heider, Dominik; Verheyen, Jens; Hoffmann, Daniel

    BMC Res Notes · 2011 · Inggris · PubMed Central

    BACKGROUND: Machine learning techniques have been widely applied to biological sequences, e.g. to predict drug resistance in HIV-1 from sequences of drug target proteins and protein functional classes. As deletions and insertions are frequent in biological sequences, a major limitation of current…

  17. Artikel Jurnal Teks lengkap

    Machine learning and complex biological data

    Xu, Chunming; Jackson, Scott A.

    Genome Biol · 2019 · Inggris · PubMed Central

    Machine learning has demonstrated potential in analyzing large, complex biological data. In practice, however, biological information is required in addition to machine learning for successful application.

  18. Artikel Jurnal Teks lengkap

    Application of Machine Learning in Microbiology

    Qu, Kaiyang; Guo, Fei; Liu, Xiangrong dkk.

    Front Microbiol · 2019 · Inggris · PubMed Central

    …of high-throughput sequencing technology. To deal with this problem, machine learning (ML) methods have been widely applied to the field of microbiology. Literature reviews have shown that ML can be used in many aspects of microbiology research, especially classification problems, and for exploring…

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