Recent Trends in Learning From Data: Tutorials from the INNS Big Data and Deep Learning Conference (INNSBDDL2019): Studies in Computational Intelligence, cartea 896
Editat de Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguitaen Limba Engleză Paperback – 4 apr 2021
Toate formatele și edițiile | Preț | Express |
---|---|---|
Paperback (1) | 908.16 lei 6-8 săpt. | |
Springer International Publishing – 4 apr 2021 | 908.16 lei 6-8 săpt. | |
Hardback (1) | 914.28 lei 6-8 săpt. | |
Springer International Publishing – 4 apr 2020 | 914.28 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783030438852
ISBN-10: 3030438856
Ilustrații: VII, 221 p. 81 illus., 55 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.33 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3030438856
Ilustrații: VII, 221 p. 81 illus., 55 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.33 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Cham, Switzerland
Cuprins
Introduction: Recent Trends in Learning From Data.- Learned data structures.- Deep Randomized Neural Networks.- Tensor Decompositions and Practical Applications.- Deep learning for graphs.- Limitations of Shallow Networks.- Fairness in Machine Learning.- Online Continual Learning on Sequences.
Textul de pe ultima copertă
This book offers a timely snapshot and extensive practical and theoretical insights into the topic of learning from data. Based on the tutorials presented at the INNS Big Data and Deep Learning Conference, INNSBDDL2019, held on April 16-18, 2019, in Sestri Levante, Italy, the respective chapters cover advanced neural networks, deep architectures, and supervised and reinforcement machine learning models. They describe important theoretical concepts, presenting in detail all the necessary mathematical formalizations, and offer essential guidance on their use in current big data research.
Caracteristici
Gathers tutorials from the 2019 INNS Big Data and Deep Learning Conference Describes cutting-edge AI-based tools and applications Offers essential guidance on the design and analysis of advanced AI-based models Blends mathematical foundations and practice-oriented insights