"Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels"

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Book	Author(s)	Year	Publisher
Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels	William W. Hsieh	2009-07	Cambridge University Press
Machine learning: neural networks, genetic algorithms, and fuzzy systems /	Adeli, Hojjat,; Hung, Shih-Lin,	[1995], ©1995.	Wiley,
MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence	Phil Kim	1st ed.	Apress
Neural Networks and Statistical Learning	Ke-Lin Du; M. N. S. Swamy	2014	Springer London
Neural Networks and Statistical Learning	Ke-Lin Du; M. N. S. Swamy	2nd ed. 2019	Springer London
Neural networks and learning machines	Haykin, Simon	2008;2009	Pearson Education
Neural Networks and Learning Machines	Simon O. Haykin	2008	Prentice Hall
Neural Networks and Learning Machines	Simon S. Haykin	2009	Prentice Hall
Machine Learning with Neural Networks: An Introduction for Scientists and Engineers	Bernhard Mehlig	2021-10	Cambridge University Press
Learning and Categorization in Modular Neural Networks	Jacob M.J. Murre	1992	Routledge
Machine Learning in Complex Networks	Thiago Christiano Silva; Liang Zhao	1st ed. 2016	Springer International Publishing
On-Line Learning in Neural Networks	David Saad	2009	Cambridge University Press
On-Line Learning in Neural Networks	David Saad	1999-01	Cambridge University Press
Delay learning in artificial neural networks	Catherine E. Myers	1992	Chapman & Hall
Evolutionary Approach to Machine Learning and Deep Neural Networks: Neuro-Evolution and Gene Regulatory Networks	Hitoshi Iba	1st ed. 2018	Springer Nature Singapore
Machine learning, neural and statistical classification /	Michie, Donald.; Spiegelhalter, D. J.; Taylor, C. C.,	1994.	Prentice Hall,
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks	Russell Reed; Robert J Marks	1999	MIT Press,
Neural smithing: supervised learning in feedforward artificial neural networks /	Reed, Russell D.; Marks, Robert J.,	[1999], ©1999.	The MIT Press,
Neural smithing: supervised learning in feedforward artificial neural networks	Russell D. Reed	1999	The MIT Press
Neural Networks and Its Learning Techniques		2014	Association of Scientists, Developers and Faculties
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Machine Learning in Neural Networks	Eugene Lin; Shih-Jen Tsai	Frontiers in Psychiatry: Artificial Intelligence, Precision Medicine, and Other Paradigm Shifts	Yong-Ku Kim	1st ed. 2019	Springer Nature Singapore
Neural Networks and Machine Learning	Richard Wiener	Generic Data Structures and Algorithms in Go: An Applied Approach Using Concurrency, Genericity and Heuristics	Richard Wiener	1st ed.	Apress
Machine Learning and Neural Networks		Visualizing technology. Complete	Debra Geoghan	2020	Pearson
Neural Networks and Other Machine Learning Methods in Cancer Research	Alfredo Vellido; Paulo J. G. Lisboa	Computational and Ambient Intelligence: 9th International Work-Conference on Artificial Neural Networks, IWANN 2007, San Sebastián, Spain, June 20-22, 2007, Proceedings	Francisco Sandoval; Alberto Prieto; Joan Cabestany; Manuel Graña	2007	Springer Berlin Heidelberg
Machine Learning, Deep Learning and Neural Networks	Evan Shellshear; Michael Tremeer; Cameron Bean	Artificial Intelligence in Medicine: Applications, Limitations and Future Directions	Manda Raz; Tam C. Nguyen; Erwin Loh	1st ed. 2022	Springer Nature Singapore
Machine Learning: Artificial Neural Networks	Donald J. Norris	Beginning Artificial Intelligence with the Raspberry Pi	Donald J. Norris	1st ed.	Apress
Neural networks and machine learning architectures		Modern Computer Architecture and Organization: Learn x86, ARM, and RISC-V architectures and the design of smartphones, PCs, and cloud servers	Jim Ledin	2022	Packt Publishing
Neural networks and machine learning architectures		Modern Computer Architecture and Organization	Jim Ledin	2020	Packt Publishing Pvt. Ltd.
Understanding machine learning and neural networks		Hands-On Vision and Behavior for Self-Driving Cars: Explore Visual Perception, Lane Detection, and Object Classification with Python 3 and OpenCV 4.	Venturi, Luca.; Korda, Krishtof.	2020.	Packt Publishing, Limited,
Introduction to Machine Learning and Neural Networks	Toby Dylan Hocking	Land Carbon Cycle Modeling: Matrix Approach, Data Assimilation, &a; Ecological Forecasting	Yiqi Luo; Benjamin Smith	2022	Routledge
Introduction of machine learning and neural networks	Zebang Shen; Binbin Yong; Peng Zhi	Theories and Practices of Self-Driving Vehicles	Binbin Yong; Peng Zhi; Qingguo Zhou; Rui Zhao andZebang Shen	2022	Elsevier
Introduction to machine learning and neural networks		Learning C++ by Building Games with Unreal Engine 4: A beginner's guide to learning 3D game development with C++ and UE4, 2nd Edition	Sharan Volin	2018	Packt Publishing
Chapter 9: Machine Learning and Neural Networks		Python Machine Learning: The Ultimate Beginner's Guide to Learn Python Machine Learning Step by Step Using Scikit-Learn and Tensorflow	Turner, Ryan	2019
Deep Neural Networks and Explainable Machine Learning	Antonio Maratea; Alessio Ferone	Fuzzy Logic and Applications: 12th International Workshop, WILF 2018, Genoa, Italy, September 6–7, 2018, Revised Selected Papers	Robert Fullér; Silvio Giove; Francesco Masulli	1st ed. 2019	Springer International Publishing
7 Machine Learning and Neural Networks 143		The essence of artificial intelligence	Alison Cawsey	1998	Prentice Hall
24 - Neural Networks for Machine Learning		Human and Machine Hearing: Extracting Meaning from Sound	Richard F. Lyon	2017-05	Cambridge University Press
Machine Learning with Shallow Neural Networks	Charu C. Aggarwal	Neural Networks and Deep Learning: A Textbook	Charu C. Aggarwal	1st ed. 2018	Springer International Publishing
Neural networks and the ascent of machine learning		Artificial intelligence: a guide for thinking humans /	Mitchell, Melanie		Picador
Corresponding machine learning algorithm - neural networks and deep learning		Healthcare analytics made simple: techniques in healthcare computing using machine learning and Python	Kumar, Vikas	2018	Packt Publishing
Learning in neural networks	J. Bernasconi	Dynamics and Stochastic Processes: Theory and Applications. Proceedings of a Workshop Held in Lisbon, Portugal October 24–29, 1988	Ricardo Lima; Ludwig Streit; Rui Vilela Mendes	1990	Springer Berlin Heidelberg
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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