Showing 20 of 622 academic articles
Claire Nédellec, Céline Rouveirol • Lecture notes in computer science
(1998)
OPENALEX
DOI: https://doi.org/10.1007/bfb0026664
Taiwo Oladipupo Ayodele • InTech eBooks
(2010)
OPENALEX
cc-by-nc-sa
DOI: https://doi.org/10.5772/9394
El‐Ghazali Talbi • ACM Computing Surveys
(2021)
During the past few years, research in applying machine learning (ML) to design efficient, effective, and robust metaheuristics has become increasingly popular. Many of those machine learning-supported metaheuristics have generated high-qua...
OPENALEX
Open Access
DOI: https://doi.org/10.1145/3459664
Christian P. Robert • CHANCE
(2014)
Kevin P. MurphyHardcover: 1104 pagesYear: 2012Publisher: The MIT PressISBN-13: 978-0262018029I have to admit the rather embarrassing fact that Machine Learning, a Probabilistic Perspective is the f......
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Open Access
DOI: https://doi.org/10.1080/09332480.2014.914768
Ethem Alpaydın • The MIT Press eBooks
(2004)
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Frank Hutter, Lars Kotthoff, Joaquin Vanschoren • The Springer series on challenges in machine learning
(2019)
This open access book gives the first comprehensive overview of general methods in Automatic Machine Learning, AutoML, collects descriptions of existing AutoML systems based on these methods, and discusses the first international challenge ...
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cc-by
DOI: https://doi.org/10.1007/978-3-030-05318-5
Geoffrey I. Webb, Claude Sammut • Springer eBooks
(2017)
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DOI: https://doi.org/10.1007/978-1-4899-7687-1
Introduzione Al Corso, Roberto Basili, Wm&r Motivazioni • Kybernetes
(2010)
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DOI: https://doi.org/10.1108/k.2010.06739hae.001
Xian‐Da Zhang • Springer eBooks
(2020)
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DOI: https://doi.org/10.1007/978-981-15-2770-8_6
Gopinath Rebala, Ajay Ravi, Sanjay Churiwala • Springer eBooks
(2019)
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DOI: https://doi.org/10.1007/978-3-030-15729-6
Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski • Kluwer international series in engineering and computer science
(1986)
OPENALEX
DOI: https://doi.org/10.1007/978-1-4613-2279-5
Shai Shalev‐Shwartz, Shai Ben-David • Cambridge University Press eBooks
(2014)
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...
OPENALEX
DOI: https://doi.org/10.1017/cbo9781107298019
David Barber • Cambridge University Press eBooks
(2012)
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...
OPENALEX
DOI: https://doi.org/10.1017/cbo9780511804779
Sendhil Mullainathan, Jann Spiess • The Journal of Economic Perspectives
(2017)
Machines are increasingly doing “intelligent” things. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the presence y of a face from pixels x. This similarity to ...
OPENALEX
DOI: https://doi.org/10.1257/jep.31.2.87
Sebastian Raschka, Vahid Mirjalili (2017)
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning tech...
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Mohssen M. Z. E. Mohammed, Muhammad Badruddin Khan, Eihab B. M. Bashier • CRC Press eBooks
(2016)
Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This...
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DOI: https://doi.org/10.1201/9781315371658
Gangadhar Shobha, Shanta Rangaswamy • Handbook of statistics
(2018)
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DOI: https://doi.org/10.1016/bs.host.2018.07.004
Marc Claesen, Bart De Moor • arXiv (Cornell University)
(2015)
We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based o...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1502.02127
Musa Gün, Ahmet Akusta, Haydar Karadağ • İstanbul İktisat Dergisi
(2025)
This study aims to examine the impact of macro-financial indicators on the housing sales volume in Türkiye and evaluate the forecasting performance of traditional time-series models versus modern machine-learning algorithms. Using monthly d...
DOAJ
Open Access (DOAJ)
DOI: 10.26650/ISTJECON2025-1707729
Heechan Han, Boran Kim, Kyunghun Kim, Donghyun Kim et al. • Water Science and Technology
(2023)
Precipitation is one of the driving forces in water cycles, and it is vital for understanding the water cycle, such as surface runoff, soil moisture, and evapotranspiration. However, missing precipitation data at the observatory becomes an ...
DOAJ
Open Access (DOAJ)
DOI: 10.2166/wst.2023.237