Libri sul tema "Machine learnings"
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Ertekin, Şeyda. Algorithms for efficient learning systems: Online and active learning approaches. Saarbrücken: VDM Verlag Dr. Müller, 2009.
Campbell, Colin. Learning with support vector machines. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2011.
Boyle, Brandon H. Support vector machines: Data analysis, machine learning, and applications. Hauppauge, N.Y: Nova Science Publishers, 2011.
Zhou, Zhi-Hua. Machine Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-1967-3.
Jung, Alexander. Machine Learning. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8193-6.
Mitchell, Tom M., Jaime G. Carbonell e Ryszard S. Michalski. Machine Learning. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2279-5.
Fernandes de Mello, Rodrigo, e Moacir Antonelli Ponti. Machine Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94989-5.
Bell, Jason. Machine Learning. Indianapolis, IN, USA: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781119183464.
Huang, Kaizhu, Haiqin Yang, Irwin King e Michael Lyu. Machine Learning. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79452-3.
Jebara, Tony. Machine Learning. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9011-2.
Phillips, Charlene. The sewing machine classroom: Learning the ins and outs of your machine. Cincinnati, OH: Krause Publications, 2011.
Lopes, Noel, e Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-06938-8.
Hutchinson, Alan. Algorithmic learning. Oxford: Clarendon Press, 1994.
Steinwart, Ingo. Support vector machines. New York: Springer, 2008.
Joachim, Diederich, a cura di. Rule extraction from support vector machines. Berlin: Springer, 2008.
Vorobeychik, Yevgeniy, e Murat Kantarcioglu. Adversarial Machine Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-01580-9.
Chen, Zhiyuan, e Bing Liu. Lifelong Machine Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-031-01581-6.
Tsihrintzis, George A., Dionisios N. Sotiropoulos e Lakhmi C. Jain, a cura di. Machine Learning Paradigms. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-94030-4.
Hutter, Frank, Lars Kotthoff e Joaquin Vanschoren, a cura di. Automated Machine Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05318-5.
Sun, Shiliang, Liang Mao, Ziang Dong e Lidan Wu. Multiview Machine Learning. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3029-2.
Zhang, Cha, e Yunqian Ma, a cura di. Ensemble Machine Learning. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-9326-7.
Tsihrintzis, George A., Maria Virvou, Evangelos Sakkopoulos e Lakhmi C. Jain, a cura di. Machine Learning Paradigms. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15628-2.
Carter, Eric, e Matthew Hurst. Agile Machine Learning. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-5107-2.
Vermeulen, Andreas François. Industrial Machine Learning. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5316-8.
Stohr, Daniel Christoph. Beruflichen Anforderungen der Digitalisierung Hinsichtlich Formaler, Physischer und Kompetenzspezifischer Aspekte: Eine Analyse Von Stellenanzeigen Mittels Methoden des Text Minings und Machine Learnings. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2019.
Stohr, Daniel Christoph. Die Beruflichen Anforderungen der Digitalisierung Hinsichtlich Formaler, Physischer und Kompetenzspezifischer Aspekte: Eine Analyse Von Stellenanzeigen Mittels Methoden des Text Minings und Machine Learnings. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2019.
Stohr, Daniel Christoph. Die Beruflichen Anforderungen der Digitalisierung Hinsichtlich Formaler, Physischer und Kompetenzspezifischer Aspekte: Eine Analyse Von Stellenanzeigen Mittels Methoden des Text Minings und Machine Learnings. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2019.
Stohr, Daniel Christoph. Die Beruflichen Anforderungen der Digitalisierung Hinsichtlich Formaler, Physischer und Kompetenzspezifischer Aspekte: Eine Analyse Von Stellenanzeigen Mittels Methoden des Text Minings und Machine Learnings. Lang GmbH, Internationaler Verlag der Wissenschaften, Peter, 2019.
Goldberg, Andrew, e Xiaojin Zhu. Introduction to Semi-Supervised Learning. Morgan & Claypool Publishers, 2009.
Goldberg, Andrew, e Xiaojin Zhu. Introduction to Semi-supervised Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning). Morgan & Claypool Publishers, 2008.
Takano, Shigeyuki. Thinking Machines: Machine Learning and Its Hardware Implementation. Elsevier Science & Technology Books, 2021.
Lopes, Noel, e Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Springer, 2016.
Lopes, Noel, e Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Springer, 2014.
Lopes, Noel, e Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - A Practical Approach. Springer, 2014.
Lopes, Noel, e Bernardete Ribeiro. Machine Learning for Adaptive Many-Core Machines - a Practical Approach. Springer, 2014.
Cholewa, Valentin. Machine-Learning Basics for Beginners : Machine Learning Methods: Enterprise Machine Learning Guide. Independently Published, 2021.
Liu, Shaowu, e Zhi-Hua Zhou. Machine Learning. Springer, 2020.
Marsland, Stephen. Machine Learning. Chapman and Hall/CRC, 2014. http://dx.doi.org/10.1201/b17476.
Mooney, Raymond J. Machine Learning. A cura di Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0020.
Zhang, Yagang, a cura di. Machine Learning. InTech, 2010. http://dx.doi.org/10.5772/217.
Machine Learning. United States: University of California, 2018. http://dx.doi.org/10.4135/9781529795417.
Machine Learning. Elsevier, 1990. http://dx.doi.org/10.1016/c2009-0-27578-7.
Machine Learning. Elsevier, 1991. http://dx.doi.org/10.1016/c2009-0-27657-4.
Machine Learning. Elsevier, 2015. http://dx.doi.org/10.1016/c2013-0-19102-7.
Machine Learning. Elsevier, 2018. http://dx.doi.org/10.1016/c2015-0-00237-4.
Machine Learning. Elsevier, 2020. http://dx.doi.org/10.1016/c2017-0-03724-2.
Machine Learning. Elsevier, 2020. http://dx.doi.org/10.1016/c2019-0-03772-7.
Kang, Minsoo, e Eunsoo Choi. Machine Learning. WORLD SCIENTIFIC, 2021. http://dx.doi.org/10.1142/12037.
Marsland, Stephen. Machine Learning. Chapman and Hall/CRC, 2011. http://dx.doi.org/10.1201/9781420067194.
Theodoridis, Sergios. Machine Learning. Elsevier Science & Technology, 2020.