AI Bibliography
AI Bibliography |
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Balakrishnan, A. (2021). Productizing an artificial intelligence solution for intelligent detail extraction—synergy of symbolic and sub-symbolic artificial intelligence techniques. Trends of Data Science and Applications: Theory and Practices, 954, 23. |
| Resource type: Journal Article BibTeX citation key: Balakrishnan2021 View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Computer Science, Data Sciences, Decision Theory, General, Mathematics Subcategories: Big data, Decision making, Deep learning, Machine learning, Markov models, Neural nets, Neurosymbolic Creators: Balakrishnan Publisher: Collection: Trends of Data Science and Applications: Theory and Practices |
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This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 710, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.
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