Bücher zum Thema „Continuous and distributed machine learning“
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Weiss, Gerhard. Distributed machine learning. Sankt Augustin: Infix, 1995.
Den vollen Inhalt der Quelle findenTestas, Abdelaziz. Distributed Machine Learning with PySpark. Berkeley, CA: Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9751-3.
Der volle Inhalt der QuelleAmini, M. Hadi, Hrsg. Distributed Machine Learning and Computing. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-57567-9.
Der volle Inhalt der QuelleJiang, Jiawei, Bin Cui und Ce Zhang. Distributed Machine Learning and Gradient Optimization. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3420-8.
Der volle Inhalt der QuelleJoshi, Gauri. Optimization Algorithms for Distributed Machine Learning. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19067-4.
Der volle Inhalt der QuelleSahoo, Jyoti Prakash, Asis Kumar Tripathy, Manoranjan Mohanty, Kuan-Ching Li und Ajit Kumar Nayak, Hrsg. Advances in Distributed Computing and Machine Learning. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4807-6.
Der volle Inhalt der QuelleRout, Rashmi Ranjan, Soumya Kanti Ghosh, Prasanta K. Jana, Asis Kumar Tripathy, Jyoti Prakash Sahoo und Kuan-Ching Li, Hrsg. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1018-0.
Der volle Inhalt der QuelleTripathy, Asis Kumar, Mahasweta Sarkar, Jyoti Prakash Sahoo, Kuan-Ching Li und Suchismita Chinara, Hrsg. Advances in Distributed Computing and Machine Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-4218-3.
Der volle Inhalt der QuelleNanda, Umakanta, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Mahasweta Sarkar und Kuan-Ching Li, Hrsg. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1841-2.
Der volle Inhalt der QuelleChinara, Suchismita, Asis Kumar Tripathy, Kuan-Ching Li, Jyoti Prakash Sahoo und Alekha Kumar Mishra, Hrsg. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1203-2.
Der volle Inhalt der QuelleNanda, Umakanta, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Mahasweta Sarkar und Kuan-Ching Li, Hrsg. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3523-5.
Der volle Inhalt der QuelleWeiß, Gerhard, Hrsg. Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-62934-3.
Der volle Inhalt der QuelleEuropean Conference on Artificial Intelligence (12th 1996 Budapest, Hungary). Distributed artificial intelligence meets machine learning: Learning in multi-agent environments : ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, 1996, ICMAS'96 Workshop LIOME, Kyoto, Japan, December 10, 1996, selected papers. Berlin: Springer, 1997.
Den vollen Inhalt der Quelle findenKim, Steven H. Learning and coordination: Enhancing agent performance through distributed decision making. Dordrecht: Kluwer Academic, 1994.
Den vollen Inhalt der Quelle findenInternational, Joint Conference on Artificial Intelligence (14th 1995 Montréal Québec). Adaption and learning in multi-agent systems: IJCAI '95 workshop, Montréal, Canada, August 21, 1995, proceedings. Berlin: Springer, 1996.
Den vollen Inhalt der Quelle findenChaturvedi, Alok R. A machine learning approach to the design of time invariant fragments for replication in a distributed database environment. West Lafayette, Ind: Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1989.
Den vollen Inhalt der Quelle findenOyarzun Laura, Cristina, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg et al., Hrsg. Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90874-4.
Der volle Inhalt der Quelle1962-, Weiss Gerhard, European Conference on Artificial Intelligence, (12th : 1996 : Budapest, Hungary) und International Conference on Multi-Agent Systems, (2nd : 1996 : Kyoto, Japan), Hrsg. Distributed artificial intelligence meets machine learning: Learning in multi-agent environments : ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, 1996, ICMAS'96 Workshop LIOME, Kyoto, Japan, December 10, 1996 : selected papers. Berlin: Springer, 1997.
Den vollen Inhalt der Quelle findenPolyakova, Anna, Tat'yana Sergeeva und Irina Kitaeva. The continuous formation of the stochastic culture of schoolchildren in the context of the digital transformation of general education. ru: INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1876368.
Der volle Inhalt der QuelleLeigh, J. R. Control Theory. 2. Aufl. Stevenage: IET, 2004.
Den vollen Inhalt der Quelle findenDistributed Machine Learning Patterns. Manning Publications Co. LLC, 2024.
Den vollen Inhalt der Quelle findenTang, Yuan. Distributed Machine Learning Patterns. Manning Publications Co. LLC, 2022.
Den vollen Inhalt der Quelle findenOptimization Algorithms for Distributed Machine Learning. Springer International Publishing AG, 2023.
Den vollen Inhalt der Quelle findenDistributed Machine Learning and Gradient Optimization. Springer, 2023.
Den vollen Inhalt der Quelle findenDistributed Machine Learning and Gradient Optimization. Springer Singapore Pte. Limited, 2021.
Den vollen Inhalt der Quelle findenLearning Ray: Flexible Distributed Python for Machine Learning. O'Reilly Media, Incorporated, 2023.
Den vollen Inhalt der Quelle findenHarini, S., und V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Den vollen Inhalt der Quelle findenHarini, S., und V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Den vollen Inhalt der Quelle findenHarini, S., und V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Den vollen Inhalt der Quelle findenHarini, S., und V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Den vollen Inhalt der Quelle findenLangford, John, Ron Bekkerman und Mikhail Bilenko. Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2011.
Den vollen Inhalt der Quelle findenLangford, John, Ron Bekkerman und Mikhail Bilenko. Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2012.
Den vollen Inhalt der Quelle findenScaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2018.
Den vollen Inhalt der Quelle findenLangford, John, Ron Bekkerman und Mikhail Bilenko. Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2012.
Den vollen Inhalt der Quelle findenScaling up machine learning: Parallel and distributed approaches. Cambridge: Cambridge University Press, 2011.
Den vollen Inhalt der Quelle findenGupta, Nirupam, und Rafael Pinot. Robust Machine Learning: Distributed Methods for Safe AI. Springer, 2024.
Den vollen Inhalt der Quelle findenWang, Guanhua. Distributed Machine Learning with Python: Accelerating Model Training and Serving with Distributed Systems. Packt Publishing, Limited, 2022.
Den vollen Inhalt der Quelle findenDistributed Machine Learning with Python: Accelerating Model Training and Serving with Distributed Systems. de Gruyter GmbH, Walter, 2022.
Den vollen Inhalt der Quelle findenDistributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers. 2010.
Den vollen Inhalt der Quelle findenDistributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers. Now Publishers, 2011.
Den vollen Inhalt der Quelle findenCollier, Rich, und Bahaaldine Azarmi. Machine Learning with the Elastic Stack: Expert Techniques to Integrate Machine Learning with Distributed Search and Analytics. Packt Publishing, Limited, 2019.
Den vollen Inhalt der Quelle findenTatarenko, Tatiana. Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems. Springer, 2017.
Den vollen Inhalt der Quelle findenTatarenko, Tatiana. Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems. Springer, 2018.
Den vollen Inhalt der Quelle findenAdvances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2021. Springer, 2022.
Den vollen Inhalt der Quelle findenLi, Kuan-Ching, Asis Kumar Tripathy, Mahasweta Sarkar, Jyoti Prakash Sahoo und Suchismita Chinara. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2020. Springer, 2020.
Den vollen Inhalt der Quelle findenLi, Kuan-Ching, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Ajit Kumar Nayak und Manoranjan Mohanty. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2021. Springer Singapore Pte. Limited, 2021.
Den vollen Inhalt der Quelle findenRout, Rashmi Ranjan, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Soumya Kanti Ghosh und Prasanta K. Jana. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2022. Springer, 2022.
Den vollen Inhalt der Quelle findenTripathy, Asis Kumar, Mahasweta Sarkar und Jyoti Prakash Sahoo. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2020. Springer, 2020.
Den vollen Inhalt der Quelle findenIozzia, Guglielmo. Hands-On Deep Learning with Apache Spark: Build and Deploy Distributed Deep Learning Applications on Apache Spark. Packt Publishing, Limited, 2019.
Den vollen Inhalt der Quelle findenGrant, Ginger, Guillermo Fernandez, Julio Granados, Pau Sempere und Javier Torrenteras. Exam Ref 70-774 Perform Cloud Data Science with Azure Machine Learning. Microsoft Press, 2018.
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