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Andreas Müller, Sarah Guido (2016)
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teac...
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Khalil A. Alruwaitee • Journal of Radiation Research and Applied Sciences
(2024)
Predictions on stock market prices are a noble task owing to huge complex, dynamic, and chaotic surroundings. Fast ups and downs arise in the stock market due to influences from foreign merchandise, such as sensitive political, stockholder,...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrras.2024.101172
Chirag Gupta, Venkategowda Ramegowda, Supratim Basu, Andy Pereira • Frontiers in Genetics
(2021)
Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRA...
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Open Access (DOAJ)
DOI: 10.3389/fgene.2021.652189
Vidya Baiju, Akshitha J, Namasiyava Naveen S • European Medical Journal
(2024)
Brain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery. The tumour can be removed...
DOAJ
Open Access (DOAJ)
DOI: 10.33590/emj/NUUC2196
Yitu Fu, Ju Xu • IEEE Access
(2019)
In this paper, we model the malware detection problem as a graph inference problem, and develop a novel belief propagation approach within a semi-supervised learning scheme that fully makes use of files' and hosts' connections to detect mal...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2948374
Ioannis Kavakiotis, O. Tsave, Athanasios Salifoglou, Nicos Maglaveras et al. • Computational and Structural Biotechnology Journal
(2017)
The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, ap...
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DOI: https://doi.org/10.1016/j.csbj.2016.12.005
PMC: 5257026
Binghui Wang, Neil Zhenqiang Gong • IEEE Symposium on Security and Privacy (S&P)
(2018)
Hyperparameters are critical in machine learning, as different hyperparameters often result in models with significantly different performance. Hyperparameters may be deemed confidential because of their commercial value and the confidentia...
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Open Access
DOI: https://doi.org/10.1109/sp.2018.00038
Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO)
(2014)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...
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DOI: https://doi.org/10.1109/micro.2014.58
Phil Kim • Apress eBooks
(2017)
However, experts generally distinguish them. If you have decided to study this field, it’s important you understand what these words actually mean, and more importantly, how they differ. These keywords were added by machine and not by the a...
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DOI: https://doi.org/10.1007/978-1-4842-2845-6_1
Sina Ardabili, Amir Hosein Mosavi, Pedram Ghamisi, Ferdinánd Filip et al. • Algorithms
(2020)
Abstract Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simpl...
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DOI: https://doi.org/10.3390/a13100249
Yagang Zhang • InTech eBooks
(2010)
The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call “learning” tasks...
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Open Access
DOI: https://doi.org/10.5772/225
Drew Conway, J.M. White • CERN Document Server (European Organization for Nuclear Research)
(2012)
If you're an experienced programmer interested in crunching data, this book will get you started with machine learning-a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John...
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Liu Yun, Oladapo Christopher Esan, Zhefei Pan, Liang An • Energy and AI
(2021)
The screening of advanced materials coupled with the modeling of their quantitative structural-activity relationships has recently become one of the hot and trending topics in energy materials due to the diverse challenges, including low su...
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DOI: https://doi.org/10.1016/j.egyai.2021.100049
Ji-Chong Yang, Yu-Chen Guo, Li-Hua Cai • Nuclear Physics B
(2022)
Anomaly detection algorithms have been proved to be useful in the search of new physics beyond the Standard Model. However, a prerequisite for using an anomaly detection algorithm is that the signal to be sought is indeed anomalous. This do...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.nuclphysb.2022.115735
Ayaz Ahmad, Fawad Ahmad, Muhammad Suleman Khan, Adel Aldalbahi • PeerJ Computer Science
(2026)
Proactive caching in multi-tier cellular networks (MTCNs) is an efficient technique for alleviating heavy data traffic on backhaul links, thereby reducing content latency and increasing the overall cache hit ratio (CHR) and user satisfactio...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj-cs.4004
Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports
(2025)
Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-19922-7
Orges Koci, Richard K. Russell, M. Guftar Shaikh, Christine Edwards et al. • Microbiome
(2024)
Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...
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Open Access (DOAJ)
DOI: 10.1186/s40168-024-01834-9
Hanjie Xu, Jian Xiong, Jinyu Wu, Xianlai Zhou et al. • Scientific Reports
(2025)
Abstract The Ivy Algorithm (IVYA), a swarm intelligence algorithm inspired by plant growth, presents a novel framework for optimization. To unlock its full potential in complex, high-dimensional problems, it is crucial to address the fundam...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-32510-z
Qingyang Ling • Applied and Computational Engineering
(2023)
Machine learning is a field of study where the computer can learn for itself without a human explicitly hardcoding the knowledge for it. These algorithms make up the backbone of machine learning. This paper aims to study the field of machin...
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DOI: https://doi.org/10.54254/2755-2721/4/20230355
Sarkar Siddique, James C. L. Chow • Encyclopedia
(2021)
Machine learning (ML) is a study of computer algorithms for automation through experience. ML is a subset of artificial intelligence (AI) that develops computer systems, which are able to perform tasks generally having need of human intelli...
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DOI: https://doi.org/10.3390/encyclopedia1010021