"Optimization for Machine Learning: Gradient Descent"

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Book	Author(s)	Year	Publisher
Distributed Machine Learning and Gradient Optimization	Jiawei Jiang; Bin Cui; Ce Zhang	1st ed. 2022	Springer Nature Singapore
Optimization and Machine Learning - Optimizationfor Machine Learning and Machine Learning for Optimization	Rachid Chelouah; Patrick Siarry	2022	John Wiley & Sons
Optimization for Machine Learning	Suvrit Sra; Sebastian Nowozin; Stephen J. Wright	2011	MIT Press,
Machine Learning and Optimization Models for Optimization in Cloud	Punit Gupta; Mayank Kumar Goyal; Sudeshna Chakraborty; Ahmed A Elngar	2022	Routledge
Stochastic Optimization for Large-scale Machine Learning	Vinod Kumar Chauhan	2021	Routledge
Accelerated Optimization for Machine Learning: First-Order Algorithms	Zhouchen Lin; Huan Li; Cong Fang	1st ed. 2020	Springer Nature Singapore
Optimization in Machine Learning and Applications	Anand J. Kulkarni; Suresh Chandra Satapathy	1st ed. 2020	Springer Nature Singapore
Nonlinear Conjugate Gradient Methods for Unconstrained Optimization	Neculai Andrei	1st ed. 2020	Springer International Publishing
Linear Algebra and Optimization for Machine Learning: A Textbook	Charu C. Aggarwal	1st ed. 2020	Springer International Publishing
First-order and Stochastic Optimization Methods for Machine Learning	Guanghui Lan	1st ed. 2020	Springer International Publishing
Machine Learning for Solar Array Monitoring, Optimization, and Control	Sunil Rao; Sameeksha Katoch; Vivek Narayanaswamy; Gowtham Muniraju; Cihan Tepedelenlioglu; Andreas Spanias		Springer International Publishing
Methods of Descent for Nondifferentiable Optimization	Krzysztof C. Kiwiel	1985	Springer Berlin Heidelberg
Methods of Descent for Nondifferentiable Optimization	Krzysztof C. Kiwiel (auth.)	1985	Springer-Verlag Berlin Heidelberg
Machine learning under a modern optimization lens /	Bertsimas, Dimitris,; Dunn, Jack
Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition	Gabbouj, Moncef.; Ince, Turker.; Kiranyaz, Serkan	2014	Springer Berlin Heidelberg : Imprint: Springer
Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition	Serkan Kiranyaz, Turker Ince, Moncef Gabbouj	2013	Springer
Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition	Serkan Kiranyaz, Turker Ince, Moncef Gabbouj (auth.)	2014	Springer-Verlag Berlin Heidelberg
Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition	Serkan Kiranyaz; Turker Ince; Moncef Gabbouj	2014	Springer Berlin Heidelberg
Hyperparameter Optimization in Machine Learning: Make Your Machine Learning and Deep Learning Models More Efficient	Tanay Agrawal	1st ed.	Apress
Conjugate Gradient Algorithms in Nonconvex Optimization	Radoslaw Pytlak	2009	Springer Berlin Heidelberg
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Optimization for Machine Learning: Gradient Descent	Ekaba Bisong	Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners	Ekaba Bisong	1st ed.	Apress
Gradient descent beyond machine learning ⁑		Dercuano	Sitaker, Kragen Javier	2019
Optimization by Gradient Descent		Context-aware ranking with factorization models	Rendle, Steffen	2014	Springer
Optimization and Gradient Descent		Practical AI on the Google Cloud Platform: Learn How to Use the Latest AI Cloud Services on the Google Cloud Platform	Micheal Lanham	2020	O'Reilly Media, Inc.
4342 Gradient Descent Optimization		Neural Networks and Computing: Learning Algorithms and Applications (Series in Electrical and Computer Engineering)	Tommy W. S. Chow	2007	World Scientific Publishing Company
524 Gradient descent optimization		Pattern Recognition and Machine Learning (Information Science and Statistics)	Christopher M. Bishop	2006	Springer Science+Business Media, LLC
Gradient Descent for Learning Parameters		The Deep Learning with Keras Workshop: Learn how to define and train neural network models with just a few lines of code	Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat	2020	Packt Publishing
Gradient Descent for Learning Parameters		Applied Deep Learning with Keras: Solve complex real-life problems with the simplicity of Keras	Bhagwat, Ritesh; Abdolahnejad, Mahla; Moocarme, Matthew	2019	Packt Publishing Limited
Gradient Descent for Learning Parameters		The Deep Learning with Keras Workshop: An Interactive Approach to Understanding Deep Learning with Keras, 2nd Edition	Matthew Moocarme, Mahla Abdolahnejad, Ritesh Bhagwat	2020	Packt Publishing
Stochastic Gradient Descent for Risk Optimization	André Gustavo Carlon; André Jacomel Torii; Rafael Holdorf Lopez; José Eduardo Souza de Cursi	Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling: Uncertainties 2020	José Eduardo Souza De Cursi	1st ed. 2021	Springer International Publishing
Learning to learn gradient descent by gradient descent		Hands-On Meta Learning with Python	Ravichandiran	2018	Packt Publishing, Limited
Learning Method: Gradient Descent		Grokking deep learning	Andrew trask	2018	Manning publication
71 Optimization Using Gradient Descent		Mathematics for machine learning	Deisenroth M.P	2019
71 Optimization Using Gradient Descent		Mathematics for Machine Learning	Marc Peter Deisenroth; A Aldo Faisal; Cheng Soon Ong	2020	Cambridge University Press
16. 3. Gradient descent optimization		Applied iterative methods /	Byrne, Charles L.,	©2008.	AK Peters,
Gradient Descent: an Optimization Hammer		A Programmer’s Introduction to Mathematics	Jeremy Kun	2018	CreateSpace Independent publishing platform
Gradient Descent: an Optimization Hammer		A Programmer’s Introduction to Mathematics	Jeremy Kun	2018	CreateSpace
Large-Scale Machine Learning with Stochastic Gradient Descent	Léon Bottou	Proceedings of COMPSTAT' 2010: 19th International Conference on Computational StatisticsParis France, August 22-27, 2010 Keynote, Invited and Contributed Papers	Yves Lechevallier; Gilbert Saporta	2010	Physica-Verlag HD
Large-scale machine learning and stochastic gradient descent		Python Machine Learning Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2	by Sebastian Raschka (Author), Vahid Mirjalili (Author)	2019	Packt
Large-scale machine learning and stochastic gradient descent		Python Machine Learning - Second Edition	Raschka, Sebastian; Mirjalili, Vahid	2017	Packt Publishing
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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