Q 315 B4 : Designing freedom, with sketches by the author.; BJL
1974
1
Q 315 W6 : The human use of human beings : cybernetics and society.; BJL
1950
1
Q 315.5 S4 : A science of goal formulation : American and Soviet discussions of cybernetics and systems theory / edited by Stuart A. Umpleby, Vadim N. Sadovsky.; BJL
1991
1
Q 320 F6 : Biotechnology : concepts and applications.; BJL
1963
1
Q 320 G2 : Bionics : the nervous system as a control system / edited by R. Gawronski.; BJL
1971
1
Q 320 T8 : Automaton theory and modeling of biological systems.; BJL
Q 325 M6 : Self-producing systems : implications and applications of autopoiesis.; BJL
1995
1
Q 325 N6 : Self-organization in nonequilibrium systems / by G. Nicolis and I. Prigogine.; BJL
1977
1
Q 325 S9 : Principles of self-organization : transactions of the University of Illinois Symposium on Self-Organization / editors, H.Von Foerster, G.W. Zopf.; BJL
1962
1
Q 325 T8 : Foundations of the theory of learning systems.; BJL
1973
1
Q325.5 .A383 2021 : Advances in machine learning and computational intelligence : proceedings of ICMLCI 2019 / Srikanta Patnaik, Xin-She Yang, Ishwar K. Sethi, editors.; Online materials
Q325.5 .B36 : Fairness and machine learning : limitations and opportunities / Solon Barocas, Moritz Hardt, and Arvind Narayanan.; BJL
2023
1
Q325.5 .C46 : Deep learning with Python / François Chollet.; BJL
2018
1
Q 325.5 C9 : An introduction to support vector machines : and other kernel-based learning methods / Nello Cristianini and John Shawe-Taylor.; BJL
2000
1
Q325.5 .D45 : Mathematics for machine learning / Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong.; BJL
2020
1
Q325.5 .F434 2022 : Federated learning : a comprehensive overview of methods and applications / Heiko Ludwig, Nathalie Baracaldo (editors).; Online materials
2022
1
Q325.5 .G47 : Hands-on machine learning with Scikit-Learn and TensorFlow; BJL
2019
1
Q325.5 .G66 2016 : Deep learning / Ian Goodfellow, Yoshua Bengio, and Aaron Courville.; BJL
2016
1
Q325.5 .H3 : Machine learning for high-risk applications : approaches to responsible AI / Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto, PhD.; BJL
Q325.5 .R64 2017 : A first course in machine learning / Simon Rogers, University of Glasgow, United Kingdom, Mark Girolami, University of Warwick, United Kingdom.; Online materials
2017
1
Q325.5 .S474 2023 : A hands-on introduction to machine learning / Chirag Shah, University of Washington.; Online materials
2023
1
Q 325.5 S5 : Kernel methods for pattern analysis / John Shawe-Taylor, Nello Cristianini.; BJL
2004
1
Q325.6 .S88 1998 : Reinforcement learning [electronic resource] / an introduction / Richard S. Sutton and Andrew G. Barto.; Online materials
1998
1
Q325.6 .S888 2018 : Reinforcement learning : an introduction / Richard S. Sutton and Andrew G. Barto.; Online materials
2018
1
Q 325.6 S9 : Reinforcement learning : an introduction / Richard S. Sutton and Andrew G. Barto.; BJL
1998
1
Q 325.75 M7 : Interpretable machine learning ; a guide for making black box models explainable / Christoph Molnar.; BJL
2022
1
Q 327 A5 : Introduction to mathematical techniques in pattern rcognition.; BJL
1972
1
Q 327 B3 : Practical approach to pattern classification.; BJL
1974
1
Q 327 B6 : Pattern recognition and machine learning / Christopher M. Bishop.; BJL
