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Special Issue "Advances in Machine Learning and Applications"
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".
Deadline for manuscript submissions: 31 May 2023 | Viewed by 7541
Special Issue Editors
2. Department of Software Engineering, Institute of Automation and Information Technologies, Satbayev University, Satpayev str., 22A, Almaty 050013, Kazakhstan
Interests: applications of machine learning; data processing; scientometrics and decision support systems
Interests: symmetry groups; lie groups; dynamic systems modeling; experimental processing; artificial intellectual technologies; information systems
Special Issues, Collections and Topics in MDPI journals
Special Issue in Symmetry: 2020 Big Data and Artificial Intelligence Conference
Special Issue in Applied Sciences: 14th International Conference on Intelligent Systems (INTELS’20)
Special Issue in Applied Sciences: Big Data: Advanced Methods, Interdisciplinary Study and Applications
Special Issue in Applied Sciences: Natural Language Processing: Approaches and Applications
Special Issue in Symmetry: Selected Papers from the 15th International Conference on Intelligent Systems (INTELS’22)
Special Issue Information
Machine learning realizes the potential inherent in the idea of artificial intelligence. The main expectation associated with machine learning is the realization of flexible, adaptive, “teachable” computational methods or algorithms. These methods provide new functions of programs and systems.
Machine learning is widely used in various practical applications. A far from complete list includes medicine, biology, chemistry, agriculture, mining, finance, industry, natural language processing, astronomy, etc. Along with applications, this field of knowledge is characterized by high dynamics of theoretical research, especially in the field of deep learning. Machine learning methods and algorithms can be divided into classical and new ones. Classical algorithms and methods are described in sufficient detail and are widely used in practice. Where researchers have access to large amounts of data, impressive results are emerging with the use of deep learning methods. New architectures of deep neural networks and their modifications for various applications appear almost daily. At the same time, despite the significant differences in algorithms and methods, many practical applications are developed using similar techniques.
The purpose of this Special Issue is to gather a collection of articles reflecting the similarities and differences of the latest applied implementations of machine learning in different areas. This will allow researchers to apply the developed machine learning cases to obtain new results in various application areas. We look forward to receiving your contributions.
Prof. Dr. Ravil Muhamedyev
Prof. Dr. Evgeny Nikulchev
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- machine learning
- deep learning
- unsupervised learning
- supervisor learning
- semi supervisor learning
- reinforcement learning
- transfer learning
- natural test processing
- speech processing
- image processing
- machine vision
- convolution neural network
- recurrent neural networks