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C. Ramírez, Michael Greenop, Lorna Ashton, Ihtesham Ur Rehman • Applied Spectroscopy Reviews
(2020)
The way to analyze data in spectroscopy has changed substantially. At the same time, data science has evolved to the point where spectroscopy can find space to be housed, adapted and be functional. The integration of the two sciences has in...
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DOI: https://doi.org/10.1080/05704928.2020.1859525
Maximilian Pichler, Florian Hartig • Methods in Ecology and Evolution
(2023)
Abstract The popularity of machine learning (ML), deep learning (DL) and artificial intelligence (AI) has risen sharply in recent years. Despite this spike in popularity, the inner workings of ML and DL algorithms are often perceived as opa...
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DOI: https://doi.org/10.1111/2041-210x.14061
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg et al. • ACM Computing Surveys
(2020)
The demand for artificial intelligence has grown significantly over the past decade, and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, to increase the qual...
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Open Access
DOI: https://doi.org/10.1145/3377454
William W. Cohen, Andrew McCallum, Sam T. Roweis (2008)
This volume contains the papers accepted to the 25th International Conference on Machine Learning (ICML 2008). ICML is the annual conference of the International Machine Learning Society (IMLS), and provides a venue for the presentation and...
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Nikita Silaparasetty • Apress eBooks
(2020)
In previous chapters, we saw what artificial intelligence is and how machine learning and deep learning techniques are used to train machines to become smart. In these next few chapters, we will learn how machines are trained to take data, ...
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DOI: https://doi.org/10.1007/978-1-4842-5967-2_5
Pariwat Ongsulee • International Conference on ICT and Knowledge Engineering
(2017)
It is increasingly recognized that artificial intelligence has been touted as a new mobile. Because of the high volume of data that being generated by devices, sensors and social media users, the machine can learn to distinguish the pattern...
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DOI: https://doi.org/10.1109/ictke.2017.8259629
Hafsa Habehh, Suril Gohel • Current Genomics
(2021)
Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) technology have brought on substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, among...
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Open Access
DOI: https://doi.org/10.2174/1389202922666210705124359
PMC: 8822225
Parliamentary Office of Science and Technology, Lorna Christie (2020)
Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that ...
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Open Access
DOI: https://doi.org/10.58248/pn633
Zhiyuan Chen, Bing Liu • Synthesis lectures on artificial intelligence and machine learning
(2018)
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DOI: https://doi.org/10.1007/978-3-031-01581-6
Konstantinos G. Liakos, Patrizia Busato, Dimitrios Moshou, Simon Pearson et al. • Sensors
(2018)
Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...
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DOI: https://doi.org/10.3390/s18082674
PMC: 6111295
Wuxin Sha, Yan Li, Shun Tang, Jie Tian et al. • InfoMat
(2021)
Abstract Polymers have been widely used in energy storage, construction, medicine, aerospace, and so on. However, the complexity of chemical composition and morphology of polymers has brought challenges to their development. Thanks to the i...
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DOI: https://doi.org/10.1002/inf2.12167
Arvind Kumar Tiwari • IGI Global eBooks
(2019)
Machine learning refers to the changes in systems that perform tasks associated with artificial intelligence. This chapter presents introduction types and application of machine learning. This chapter also presents the basic concepts relate...
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DOI: https://doi.org/10.4018/978-1-7998-0414-7.ch003
William W. Cohen, Andrew Moore (2006)
This volume, which is also available from http://www.machinelearning.org, the home page of the International Machine Learning Society, contains the technical papers accepted for presentation at ICML-2006, the 23rd International Conference o...
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Rohit Kumar • Apress eBooks
(2017)
Taking our AI discussion further from Chapter 3, we will discuss here further a special type of artificial intelligence called machine learning....
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DOI: https://doi.org/10.1007/978-1-4842-3069-5_4
Stephen J. Goodswen, Joel Barratt, Paul J Kennedy, Alexa Kaufer et al. • FEMS Microbiology Reviews
(2021)
To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial intelligence applica...
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DOI: https://doi.org/10.1093/femsre/fuab015
PMC: 8498514
Vijaya B. Kolachalama, Priya S. Garg • npj Digital Medicine
(2018)
Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and othe...
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DOI: https://doi.org/10.1038/s41746-018-0061-1
PMC: 6550167
Rene Y Choi, Aaron S. Coyner, Jayashree Kalpathy–Cramer, Michael F Chiang et al. • PubMed Central
(2020)
Purpose: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. Methods: A systematic literature search in PubMed was ...
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cc-by-nc-nd
DOI: https://doi.org/10.1167/tvst.9.2.14
PMC: 7347027
Joseph A. Cruz, David Scott Wishart • Cancer Informatics
(2006)
Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, ...
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cc-by-nc
DOI: https://doi.org/10.1177/117693510600200030
PMC: 2675494
David John Lary, Amir H. Alavi, Amir H. Gandomi, Annette L. Walker • Geoscience Frontiers
(2015)
Learning incorporates a broad range of complex procedures. Machine learning (ML) is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine...
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DOI: https://doi.org/10.1016/j.gsf.2015.07.003
Dana Pessach, Erez Shmueli • ACM Computing Surveys
(2022)
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...
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DOI: https://doi.org/10.1145/3494672