Libros sobre el tema "Probability learning"
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Batanero, Carmen, Egan J. Chernoff, Joachim Engel, Hollylynne S. Lee y 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 completoDasGupta, 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 completoPeck, Roxy. Statistics: Learning from data. Australia: Brooks/Cole, Cengage Learning, 2014.
Buscar texto completoUnpingco, 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 completoUnpingco, 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 completoUnpingco, 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 completoPowell, Warren B. Optimal learning. Hoboken, New Jersey: Wiley, 2012.
Buscar texto completoVapnik, Vladimir Naumovich. The Nature of Statistical Learning Theory. New York, NY: Springer New York, 1995.
Buscar texto completoDasGupta, Anirban. Probability for statistics and machine learning: Fundamentals and advanced topics. New York: Springer, 2011.
Buscar texto completoWan, Shibiao. Machine learning for protein subcellular localization prediction. Boston: De Gruyter, 2015.
Buscar texto completoVelleman, Paul F. Learning data analysis with Data desk. New York: W.H. Freeman, 1993.
Buscar texto completoVelleman, Paul F. Learning data analysis with Data desk. New York: W.H. Freeman, 1989.
Buscar texto completoLim, 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.
Buscar texto completoGabbay, Dov M. Abductive Reasoning and Learning. Dordrecht: Springer Netherlands, 2000.
Buscar texto completoSumma, Mireille Gettler. Statistical learning and data science. Boca Raton: CRC Press, 2012.
Buscar texto completoPalfrey, 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.
Buscar texto completoRasmussen, Carl Edward. Gaussian processes for machine learning. Cambridge, Mass: MIT Press, 2006.
Buscar texto completoRasmussen, Carl Edward. Gaussian processes for machine learning. Cambridge, MA: MIT Press, 2005.
Buscar texto completoVidyasagar, M. Learning and Generalisation: With Applications to Neural Networks. London: Springer London, 2003.
Buscar texto completoDehmer, Matthias. Statistical and machine learning approaches for network analysis. Hoboken, N.J: Wiley, 2012.
Buscar texto completoBerk, Richard. Criminal Justice Forecasts of Risk: A Machine Learning Approach. New York, NY: Springer New York, 2012.
Buscar texto completoThathachar, Mandayam A. L. Networks of learning automata: Techniques for online stochastic optimization. Boston: Kluwer Academic, 2004.
Buscar texto completoThathachar, Mandayam A. L. Networks of learning automata: Techniques for online stochastic optimization. Boston, MA: Kluwer Academic, 2003.
Buscar texto completoEveritt, Brian. The analysis of contingency tables. 2a ed. London: Chapman & Hall, 1992.
Buscar texto completoKoltchinskii, Vladimir. Oracle inequalities in empirical risk minimization and sparse recovery problems: École d'été de probabilités de Saint-Flour XXXVIII-2008. Berlin: Springer Verlag, 2011.
Buscar texto completoBaram, Yoram. Estimation and classification by sigmoids based on mutual information. [Washington, D.C: National Aeronautics and Space Administration, 1994.
Buscar texto completoDietrich, Albert, ed. Knowledge structures. Berlin: Springer-Verlag, 1994.
Buscar texto completoSanner, Scott. Recent Advances in Reinforcement Learning: 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoFlach, Peter A. Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoFlach, Peter A. Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Buscar texto completoPeck, Roxy y Chris Olsen. Statistics: Learning from Data. Brooks/Cole, 2013.
Buscar texto completoPeck, Roxy y Tom Short. Statistics: Learning from Data. Brooks/Cole, 2017.
Buscar texto completoUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer, 2019.
Buscar texto completoUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer International Publishing AG, 2022.
Buscar texto completoUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer, 2016.
Buscar texto completoUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer London, Limited, 2016.
Buscar texto completoUnpingco, José. Python for Probability, Statistics, and Machine Learning. Springer, 2020.
Buscar texto completoPeck, Roxy. Statistics: Learning from Data. Cengage Learning, 2023.
Buscar texto completoPeck, Roxy. Statistics: Learning from Data. Brooks/Cole, 2013.
Buscar texto completoThe Art of Statistics: Learning from Data. Pelican Books, 2019.
Buscar texto completoThe Art of Statistics: Learning from Data. Great Britain: Pelican Books, 2019.
Buscar texto completoResearch Institute for Advanced Computer Science (U.S.), ed. Bayesian learning. [Moffett Field, Calif.]: Research Institute for Advanced Computer Science, NASA Ames Research Center, 1989.
Buscar texto completoKnox, Steven W. Machine Learning: a Concise Introduction (Wiley Series in Probability and Statistics). Wiley, 2018.
Buscar texto completoJones, Graham A. Exploring Probability in School: Challenges for Teaching and Learning. Springer, 2010.
Buscar texto completoBatanero, Carmen y Egan J. Chernoff. Teaching and Learning Stochastics: Advances in Probability Education Research. Springer, 2018.
Buscar texto completoJones, Graham A. Exploring Probability in School: Challenges for Teaching and Learning. Springer, 2005.
Buscar texto completoBatanero, Carmen y Egan J. Chernoff. Teaching and Learning Stochastics: Advances in Probability Education Research. Springer, 2019.
Buscar texto completoDuerr, Oliver y Beate Sick. Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability. Manning Publications Co. LLC, 2020.
Buscar texto completoERIC 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.
Buscar texto completoDuerr, Oliver, Beate Sick y Elvis Murina. Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability. Manning Publications, 2020.
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