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Machine Learning for Computational Science and Engineering
Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of computational procedures, analysis and accelerate the design to analysis time.
- 主办单位： Springer Nature
- 出版周期： 年刊
- 国际标准连续出版物号/电子版： ISSN 3005-1428 / EISSN 3005-1436
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