PART OF IntechOpen Book Series: Artificial Intelligence
ISSN 2633-1403
Research Topic on Machine Learning and Data Mining - always open for submissions, with an Annual Volume published each calendar year with a dedicated ISSN and ISBN.
Led by Topic Editor Dr. Marco Antonio Aceves-Fernández and an international Editorial Board, all submissions are peer-reviewed and published immediately after acceptance.
The scope of machine learning and data mining is immense and is growing every day. It has become a massive part of our daily lives, making predictions based on experience, making this a fascinating area that solves problems that otherwise would not be possible or easy to solve. This topic aims to encompass algorithms that learn from experience (supervised and unsupervised), improve their performance over time and enable machines to make data-driven decisions. It is not limited to any particular applications, but contributions are encouraged from all disciplines.
keywords
Intelligent Systems Machine Learning Data Science Data Mining Artificial Intelligence
Topic Editor
Marco Antonio Aceves-Fernández
Universidad Autonoma de Queretaro, Mexico
Part of book series
Publication details
BOOK SERIES DOI 10.5772/intechopen.79920
ISSN 2633-1403
INDEXED IN
Contribute your work to the Topic Machine Learning and Data Mining, always open for submissions. Your work will be published as part of the Annual Volume 2024, with a dedicated ISSN and ISBN.
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Your work should
Be 10 to 20 pages longProvide a context-setting introductionHave at least one section and subsectionShow original research from your fieldInclude referencesFollow our Author Guidelines and Template Guidelines
3 months to publication
Always Open for Submissions
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ISSN + ISBN
Publishing process
£1400 Chapter - Book Series Topic (Annual Volume)
It’s due only after the Editor accepts your work for publication
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You can read the guide here.
Work at your own pace with no cutoff date for submitting your work
Robust peer-review ensures your work is suitable for publication and of interest to the scientific community
Early online publication after acceptance assures research is made available to the scientific community without delay
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The opportunity to work with a prestigious publisher allows for the possibility to collaborate with more research groups interested in animal nutrition, leading to the development of new feeding strategies and food valuation while being more sustainable with the environment, allowing more readers to learn about the subject.
Universidad Autónoma del Estado de México
Mexico
If you have any questions about publishing in IntechOpen Book Series or submitting your research, our team will be happy to help. Please contact us at book.series.ai@intechopen.com
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