Libros sobre el tema "Continuous and distributed machine learning"
Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros
Consulte los 50 mejores mejores libros para su investigación sobre el tema "Continuous and distributed machine learning".
Junto a cada fuente en la lista de referencias hay un botón "Agregar a la bibliografía". Pulsa este botón, y generaremos automáticamente la referencia bibliográfica para la obra elegida en el estilo de cita que necesites: APA, MLA, Harvard, Vancouver, Chicago, etc.
También puede descargar el texto completo de la publicación académica en formato pdf y leer en línea su resumen siempre que esté disponible en los metadatos.
Explore libros sobre una amplia variedad de disciplinas y organice su bibliografía correctamente.
Weiss, Gerhard. Distributed machine learning. Sankt Augustin: Infix, 1995.
Buscar texto completoTestas, Abdelaziz. Distributed Machine Learning with PySpark. Berkeley, CA: Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9751-3.
Texto completoAmini, M. Hadi, ed. Distributed Machine Learning and Computing. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-57567-9.
Texto completoJiang, Jiawei, Bin Cui y Ce Zhang. Distributed Machine Learning and Gradient Optimization. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3420-8.
Texto completoJoshi, Gauri. Optimization Algorithms for Distributed Machine Learning. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19067-4.
Texto completoSahoo, Jyoti Prakash, Asis Kumar Tripathy, Manoranjan Mohanty, Kuan-Ching Li y Ajit Kumar Nayak, eds. Advances in Distributed Computing and Machine Learning. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4807-6.
Texto completoRout, Rashmi Ranjan, Soumya Kanti Ghosh, Prasanta K. Jana, Asis Kumar Tripathy, Jyoti Prakash Sahoo y Kuan-Ching Li, eds. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1018-0.
Texto completoTripathy, Asis Kumar, Mahasweta Sarkar, Jyoti Prakash Sahoo, Kuan-Ching Li y Suchismita Chinara, eds. Advances in Distributed Computing and Machine Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-4218-3.
Texto completoNanda, Umakanta, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Mahasweta Sarkar y Kuan-Ching Li, eds. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1841-2.
Texto completoChinara, Suchismita, Asis Kumar Tripathy, Kuan-Ching Li, Jyoti Prakash Sahoo y Alekha Kumar Mishra, eds. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1203-2.
Texto completoNanda, Umakanta, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Mahasweta Sarkar y Kuan-Ching Li, eds. Advances in Distributed Computing and Machine Learning. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3523-5.
Texto completoWeiß, Gerhard, ed. 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.
Texto completoEuropean 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.
Buscar texto completoKim, Steven H. Learning and coordination: Enhancing agent performance through distributed decision making. Dordrecht: Kluwer Academic, 1994.
Buscar texto completoInternational, 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.
Buscar texto completoChaturvedi, 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.
Buscar texto completoOyarzun Laura, Cristina, M. Jorge Cardoso, Michal Rosen-Zvi, Georgios Kaissis, Marius George Linguraru, Raj Shekhar, Stefan Wesarg et al., eds. 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.
Texto completo1962-, Weiss Gerhard, European Conference on Artificial Intelligence, (12th : 1996 : Budapest, Hungary) y International Conference on Multi-Agent Systems, (2nd : 1996 : Kyoto, Japan), eds. 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.
Buscar texto completoPolyakova, Anna, Tat'yana Sergeeva y 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.
Texto completoLeigh, J. R. Control Theory. 2a ed. Stevenage: IET, 2004.
Buscar texto completoDistributed Machine Learning Patterns. Manning Publications Co. LLC, 2024.
Buscar texto completoTang, Yuan. Distributed Machine Learning Patterns. Manning Publications Co. LLC, 2022.
Buscar texto completoOptimization Algorithms for Distributed Machine Learning. Springer International Publishing AG, 2023.
Buscar texto completoDistributed Machine Learning and Gradient Optimization. Springer, 2023.
Buscar texto completoDistributed Machine Learning and Gradient Optimization. Springer Singapore Pte. Limited, 2021.
Buscar texto completoLearning Ray: Flexible Distributed Python for Machine Learning. O'Reilly Media, Incorporated, 2023.
Buscar texto completoHarini, S. y V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Buscar texto completoHarini, S. y V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Buscar texto completoHarini, S. y V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Buscar texto completoHarini, S. y V. Pattabiraman. Scalable and Distributed Machine Learning and Deep Learning Patterns. IGI Global, 2023.
Buscar texto completoLangford, John, Ron Bekkerman y Mikhail Bilenko. Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2011.
Buscar texto completoLangford, John, Ron Bekkerman y Mikhail Bilenko. Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2012.
Buscar texto completoScaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2018.
Buscar texto completoLangford, John, Ron Bekkerman y Mikhail Bilenko. Scaling up Machine Learning: Parallel and Distributed Approaches. Cambridge University Press, 2012.
Buscar texto completoScaling up machine learning: Parallel and distributed approaches. Cambridge: Cambridge University Press, 2011.
Buscar texto completoGupta, Nirupam y Rafael Pinot. Robust Machine Learning: Distributed Methods for Safe AI. Springer, 2024.
Buscar texto completoWang, Guanhua. Distributed Machine Learning with Python: Accelerating Model Training and Serving with Distributed Systems. Packt Publishing, Limited, 2022.
Buscar texto completoDistributed Machine Learning with Python: Accelerating Model Training and Serving with Distributed Systems. de Gruyter GmbH, Walter, 2022.
Buscar texto completoDistributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers. 2010.
Buscar texto completoDistributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers. Now Publishers, 2011.
Buscar texto completoCollier, Rich y Bahaaldine Azarmi. Machine Learning with the Elastic Stack: Expert Techniques to Integrate Machine Learning with Distributed Search and Analytics. Packt Publishing, Limited, 2019.
Buscar texto completoTatarenko, Tatiana. Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems. Springer, 2017.
Buscar texto completoTatarenko, Tatiana. Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems. Springer, 2018.
Buscar texto completoAdvances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2021. Springer, 2022.
Buscar texto completoLi, Kuan-Ching, Asis Kumar Tripathy, Mahasweta Sarkar, Jyoti Prakash Sahoo y Suchismita Chinara. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2020. Springer, 2020.
Buscar texto completoLi, Kuan-Ching, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Ajit Kumar Nayak y Manoranjan Mohanty. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2021. Springer Singapore Pte. Limited, 2021.
Buscar texto completoRout, Rashmi Ranjan, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Soumya Kanti Ghosh y Prasanta K. Jana. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2022. Springer, 2022.
Buscar texto completoTripathy, Asis Kumar, Mahasweta Sarkar y Jyoti Prakash Sahoo. Advances in Distributed Computing and Machine Learning: Proceedings of ICADCML 2020. Springer, 2020.
Buscar texto completoIozzia, Guglielmo. Hands-On Deep Learning with Apache Spark: Build and Deploy Distributed Deep Learning Applications on Apache Spark. Packt Publishing, Limited, 2019.
Buscar texto completoGrant, Ginger, Guillermo Fernandez, Julio Granados, Pau Sempere y Javier Torrenteras. Exam Ref 70-774 Perform Cloud Data Science with Azure Machine Learning. Microsoft Press, 2018.
Buscar texto completo