Книги з теми "Deep learning with uncertainty"
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Marchau, Vincent A. W. J., Warren E. Walker, Pieter J. T. M. Bloemen, and Steven W. Popper, eds. Decision Making under Deep Uncertainty. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05252-2.
Saefken, Benjamin, Alexander Silbersdorff, and Christoph Weisser, eds. Learning deep. Göttingen: Göttingen University Press, 2020. http://dx.doi.org/10.17875/gup2020-1338.
Bishop, Christopher M., and Hugh Bishop. Deep Learning. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-45468-4.
Kruse, René-Marcel, Benjamin Säfken, Alexander Silbersdorff, and Christoph Weisser, eds. Learning Deep Textwork. Göttingen: Göttingen University Press, 2021. http://dx.doi.org/10.17875/gup2021-1608.
Rodriguez, Andres. Deep Learning Systems. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-031-01769-8.
Fergus, Paul, and Carl Chalmers. Applied Deep Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04420-5.
Calin, Ovidiu. Deep Learning Architectures. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36721-3.
El-Amir, Hisham, and Mahmoud Hamdy. Deep Learning Pipeline. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5349-6.
Matsushita, Kayo, ed. Deep Active Learning. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5660-4.
Michelucci, Umberto. Applied Deep Learning. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3790-8.
Moons, Bert, Daniel Bankman, and Marian Verhelst. Embedded Deep Learning. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99223-5.
Wani, M. Arif, Mehmed Kantardzic, and Moamar Sayed-Mouchaweh, eds. Deep Learning Applications. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1816-4.
Dong, Hao, Zihan Ding, and Shanghang Zhang, eds. Deep Reinforcement Learning. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4095-0.
Kim, Phil. MATLAB Deep Learning. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2845-6.
Sewak, Mohit. Deep Reinforcement Learning. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8285-7.
Gamba, Jonah. Deep Learning Models. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9672-8.
Jo, Taeho. Deep Learning Foundations. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32879-4.
Singaram, Jayakumar, S. S. Iyengar, and Azad M. Madni. Deep Learning Networks. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-39244-3.
Enrique, Castillo. Expert systems: Uncertainty and learning. Southampton: Computational Mechanics, 1991.
Hu, Fei, and Xiali Hei. AI, Machine Learning and Deep Learning. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003187158.
Ketkar, Nikhil, and Jojo Moolayil. Deep Learning with Python. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-5364-9.
Kim, Kwangjo, and Harry Chandra Tanuwidjaja. Privacy-Preserving Deep Learning. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3764-3.
Benois-Pineau, Jenny, and Akka Zemmari, eds. Multi-faceted Deep Learning. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74478-6.
Ye, Jong Chul. Geometry of Deep Learning. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6046-7.
Ahmed, Khaled R., and Henry Hexmoor, eds. Blockchain and Deep Learning. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95419-2.
Betti, Alessandro, Marco Gori, and Stefano Melacci. Deep Learning to See. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90987-1.
Betti, Alessandro, Marco Gori, and Stefano Melacci. Deep Learning to See. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90987-1.
Paluszek, Michael, Stephanie Thomas, and Eric Ham. Practical MATLAB Deep Learning. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-7912-0.
Wani, M. Arif, Farooq Ahmad Bhat, Saduf Afzal, and Asif Iqbal Khan. Advances in Deep Learning. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-6794-6.
Michelucci, Umberto. Advanced Applied Deep Learning. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4976-5.
Paluszek, Michael, and Stephanie Thomas. Practical MATLAB Deep Learning. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5124-9.
Salvaris, Mathew, Danielle Dean, and Wee Hyong Tok. Deep Learning with Azure. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3679-6.
Bhanu, Bir, and Ajay Kumar, eds. Deep Learning for Biometrics. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61657-5.
Ghatak, Abhijit. Deep Learning with R. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-5850-0.
Skansi, Sandro. Introduction to Deep Learning. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73004-2.
Ketkar, Nikhil. Deep Learning with Python. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2766-4.
Amaratunga, Thimira. Deep Learning on Windows. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6431-7.
Chen, Yen-Wei, and Lakhmi C. Jain, eds. Deep Learning in Healthcare. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-32606-7.
Tanaka, Akinori, Akio Tomiya, and Koji Hashimoto. Deep Learning and Physics. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6108-9.
Bruno, Michael A. Error and Uncertainty in Diagnostic Radiology. Oxford University Press, 2019. http://dx.doi.org/10.1093/med/9780190665395.001.0001.
Tutino, Stefania. Uncertainty in Post-Reformation Catholicism. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190694098.001.0001.
Walker, Warren E., Steven W. Popper, and Pieter J T M Bloemen. Decision Making Under Deep Uncertainty. Saint Philip Street Press, 2020.
Walker, Warren E., Steven W. Popper, and Pieter J T M Bloemen. Decision Making Under Deep Uncertainty. Saint Philip Street Press, 2020.
Wang, Xizhao, and Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Wang, Xizhao, and Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Wang, Xizhao, and Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2020.
Wang, Xizhao, and Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Wang, Xizhao, and Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Wang, Xizhao, and Junhai Zhai. Learning with Uncertainty. Taylor & Francis Group, 2016.
Kelleher, John D. Deep Learning. MIT Press, 2019.