| 书目名称 | Cracking the Machine Learning Code: Technicality or Innovation? | | 编辑 | KC Santosh,Rodrigue Rizk,Siddhi K. Bajracharya | | 视频video | | | 概述 | Covers three primary data types: numerical, textual, and image data.Offers GitHub source code encompassing fundamental components and advanced machine learning tools.Serves as a reference for research | | 丛书名称 | Studies in Computational Intelligence | | 图书封面 |  | | 描述 | .Employing off-the-shelf machine learning models is not an innovation. The journey through technicalities and innovation in the machine learning field is ongoing, and we hope this book serves as a compass, guiding the readers through the evolving landscape of artificial intelligence. It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability. Innovation in building machine learning models involves a continuous cycle of exploration, experimentation, and improvement, with a focus on pushing the boundaries of what is achievable while considering ethical implications and real-world applicability. The book is aimed at providing a clear guidance that one should not be limited to building pre-trained models to solve problems using the off-the-self basic building blocks. With primarily three different data types: numerical, textual, and image data, we offer practical applications such as predictive analysis for finance and housing, text mining from med | | 出版日期 | Book 2024 | | 关键词 | Machine Learning; Big Data; Shallow Learning; Deep Learning; Data Preprocessing; Regression Analysis; Natu | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-97-2720-9 | | isbn_softcover | 978-981-97-2722-3 | | isbn_ebook | 978-981-97-2720-9Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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发表于 2025-3-21 19:49:31
