Livros sobre o tema "Probability learning"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Veja os 50 melhores livros para estudos sobre o assunto "Probability learning".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Veja os livros das mais diversas áreas científicas e compile uma bibliografia correta.
Batanero, Carmen, Egan J. Chernoff, Joachim Engel, Hollylynne S. Lee e Ernesto Sánchez. Research on Teaching and Learning Probability. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31625-3.
Texto completo da fonteDasGupta, Anirban. Probability for Statistics and Machine Learning. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9634-3.
Texto completo da fonteAggarwal, Charu C. Probability and Statistics for Machine Learning. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-53282-5.
Texto completo da fonteEgan, J. Chernoff, Engel Joachim, Lee Hollylynne S e Sánchez Ernesto, eds. Research on Teaching and Learning Probability. Cham: Springer, 2016.
Encontre o texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18545-9.
Texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30717-6.
Texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04648-3.
Texto completo da fontePowell, Warren B. Optimal learning. Hoboken, New Jersey: Wiley, 2012.
Encontre o texto completo da fontePeck, Roxy. Statistics: Learning from data. Australia: Brooks/Cole, Cengage Learning, 2014.
Encontre o texto completo da fonteKnez, Igor. To know what to know before knowing: Acquisition of functional rules in probabilistic ecologies. Uppsala: Uppsala University, 1992.
Encontre o texto completo da fonteResearch Institute for Advanced Computer Science (U.S.), ed. Bayesian learning. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1989.
Encontre o texto completo da fonteERIC Clearinghouse for Science, Mathematics, and Environmental Education., ed. Resources for teaching and learning about probability and statistics. [Columbus, Ohio]: ERIC Clearinghouse for Science, Mathematics and Environmental Education, 1999.
Encontre o texto completo da fonteauthor, Mak M. W., ed. Machine learning for protein subcellular localization prediction. Boston: De Gruyter, 2015.
Encontre o texto completo da fonteVapnik, Vladimir Naumovich. The Nature of Statistical Learning Theory. New York, NY: Springer New York, 1995.
Encontre o texto completo da fonteDasGupta, Anirban. Probability for statistics and machine learning: Fundamentals and advanced topics. New York: Springer, 2011.
Encontre o texto completo da fonteJin, Tiantian. Effect on Superficial Variability of Examples on Learning Applied Probability. [New York, N.Y.?]: [publisher not identified], 2018.
Encontre o texto completo da fonteVelleman, Paul F. Learning data analysis with Data desk. New York: W.H. Freeman, 1993.
Encontre o texto completo da fonteLim, Chee Peng. An incremental adaptive network for on-line, supervised learning and probability estimation. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1995.
Encontre o texto completo da fonteGabbay, Dov M. Abductive Reasoning and Learning. Dordrecht: Springer Netherlands, 2000.
Encontre o texto completo da fontePalfrey, Thomas R. Testing game-theoretic models of free riding: New evidence on probability bias and learning. Cambridge, Mass: Dept. of Economics, Massachusetts Institute of Technology, 1990.
Encontre o texto completo da fonteI, Williams Christopher K., ed. Gaussian processes for machine learning. Cambridge, Mass: MIT Press, 2006.
Encontre o texto completo da fonteRasmussen, Carl Edward. Gaussian processes for machine learning. Cambridge, MA: MIT Press, 2005.
Encontre o texto completo da fonteVidyasagar, M. Learning and Generalisation: With Applications to Neural Networks. London: Springer London, 2003.
Encontre o texto completo da fonte1945-, Basak Subhash C., ed. Statistical and machine learning approaches for network analysis. Hoboken, N.J: Wiley, 2012.
Encontre o texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer, 2016.
Encontre o texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer, 2020.
Encontre o texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer, 2019.
Encontre o texto completo da fonteUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer London, Limited, 2016.
Encontre o texto completo da fontePython for Probability, Statistics, and Machine Learning. Springer International Publishing AG, 2023.
Encontre o texto completo da fontePython for Probability, Statistics, and Machine Learning. Springer International Publishing AG, 2022.
Encontre o texto completo da fontePeck, Roxy, e Chris Olsen. Statistics: Learning from Data. Brooks/Cole, 2013.
Encontre o texto completo da fontePeck, Roxy. Statistics: Learning from Data. Brooks/Cole, 2017.
Encontre o texto completo da fontePeck, Roxy. Statistics: Learning from Data. Brooks/Cole, 2013.
Encontre o texto completo da fontePeck, Roxy. Statistics: Learning from Data. Cengage Learning, 2023.
Encontre o texto completo da fonteProbability and Statistics for Machine Learning: A Textbook. Springer, 2024.
Encontre o texto completo da fonteSchrope, Byron. Probability and Its Concepts: Give Your Business an Edge by Learning More about Probability. Independently Published, 2022.
Encontre o texto completo da fonteKnox, Steven W. Machine Learning: a Concise Introduction (Wiley Series in Probability and Statistics). Wiley, 2018.
Encontre o texto completo da fonteDuerr, Oliver, Beate Sick e Elvis Murina. Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability. Manning Publications, 2020.
Encontre o texto completo da fonteBatanero, Carmen, e Egan J. Chernoff. Teaching and Learning Stochastics: Advances in Probability Education Research. Springer, 2018.
Encontre o texto completo da fonteBatanero, Carmen, e Egan J. Chernoff. Teaching and Learning Stochastics: Advances in Probability Education Research. Springer, 2019.
Encontre o texto completo da fonteTomar, Simit. Probability and Statistics for Data Science and Machine Learning. Independently Published, 2020.
Encontre o texto completo da fonteDuerr, Oliver, e Beate Sick. Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability. Manning Publications Co. LLC, 2020.
Encontre o texto completo da fonteJones, Graham A. Exploring Probability in School: Challenges for Teaching and Learning. Springer, 2010.
Encontre o texto completo da fonteJones, Graham A. Exploring Probability in School: Challenges for Teaching and Learning. Springer, 2005.
Encontre o texto completo da fonteAdams, Christopher P. Learning Microeconometrics with R. Taylor & Francis Group, 2020.
Encontre o texto completo da fonteLearning Microeconometrics with R. Taylor & Francis Group, 2020.
Encontre o texto completo da fonteDasGupta, Anirban. Probability for Statistics and Machine Learning: Fundamentals and Advanced Topics. Springer, 2013.
Encontre o texto completo da fonteMachine learning: A probabilistic perspective. Cambridge, MA: MIT Press, 2012.
Encontre o texto completo da fonteMurphy, Kevin P. Machine Learning: A Probabilistic Perspective. MIT Press, 2012.
Encontre o texto completo da fonteMurphy, Kevin P. Machine Learning: A Probabilistic Perspective. MIT Press, 2012.
Encontre o texto completo da fonte