"Learning Theory: From Regression to Classification"

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Book	Author(s)	Year	Publisher
Statistical Regression and Classification: From Linear Models to Machine Learning	Norman Matloff	2017	Routledge
Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning	Alan J. Izenman	2008	Springer New York
Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning	Alan J. Izenman (auth.)	2008	Springer-Verlag New York
Tensorflow for Deep Learning: From Linear Regression to Reinforcement Learning	Bharath Ramsundar	2018	O'Reilly Media
Classification And Regression Trees	Leo Breiman	1984	Routledge
Statistical Learning from a Regression Perspective	Richard A. Berk	2008	Springer New York
Statistical Learning from a Regression Perspective	Richard A. Berk	3rd ed. 2020	Springer International Publishing
Statistical Learning from a regression perspective	Richard A. Berk (auth.)	2008	Springer-Verlag New York
Statistical learning from a regression perspective	Berk, Richard A	2016;2020	Springer
Statistical Learning from a Regression Perspective	Richard A. Berk (auth.)	2016	Springer International Publishing
Statistical Learning from a Regression Perspective	Richard A. Berk	2nd ed. 2016	Springer International Publishing
Learning Systems: From Theory to Practice	Vassil Sgurev; Vincenzo Piuri; Vladimir Jotsov	1st ed. 2018	Springer International Publishing
Motor learning: from theory to practice	Loretta M. Stallings	1982	C.V. Mosby
Understanding Machine Learning: From Theory to Algorithms	Shai Shalev-Shwartz; Shai Ben-David	2014-05	Cambridge University Press
Learning Regression Analysis by Simulation	Kunio Takezawa (auth.)	2014	Springer Japan
Learning Regression Analysis by Simulation	Kunio Takezawa	2014	Springer Japan
Using Classification And Regression Trees: A Practical Primer	Xin Ma	2018	Information Age Publishing
Asymptotic Theory of Nonlinear Regression	A.A. Ivanov	1997	Springer Netherlands
Quantile Regression - Theory and Applications	Cristina Davino	2013	John Wiley & Sons
Machine Learning in Finance: From Theory to Practice	Matthew F. Dixon; Igor Halperin; Paul Bilokon	1st ed. 2020	Springer International Publishing
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Showing 1 to 20 of 100 entries

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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Learning Theory: From Regression to Classification	Qiang Wu; Yiming Ying; Ding-Xuan Zhou	Topics in Multivariate Approximation and Interpolation	Kurt Jetter; Martin D. Buhmann; Werner Haussmann; Robert Schaback; Joachim Stöckler	2006	Elsevier
Classification & Regression using Supervised Learning		Artificial Intelligence with Python	Prateek Joshi	2017	Packt Publishing
Supervised Learning – Classification and Regression		Structural Health Monitoring - A Machine Learning Perspective	Charles R. Farrar	2012	John Wiley & Sons
From Linear Regression to Deep Learning		Analytical Skills for AI and Data Science: Building Skills for an AI-Driven Enterprise	Daniel Vaughan	2020	O'Reilly Media
Transitioning from classification trees to regression trees		Python Machine Learning By Example: Implement machine learning algorithms and techniques to build intelligent systems, 2nd Edition	Yuxi (Hayden) Liu	2019-02-28	Packt Publishing, Limited
Transitioning from classification trees to regression trees		Python Machine Learning By Example	Yuxi Liu	2020	Packt Publishing, Limited
Concepts of Learning, Classification, and Regression	Krzysztof J. Cios; Roman W. Swiniarski; Witold Pedrycz; Lukasz A. Kurgan	Data Mining: A Knowledge Discovery Approach	Krzysztof J. Cios; Roman W. Swiniarski; Witold Pedrycz; Lukasz A. Kurgan	2007	Springer US
Deep Learning for Regression and Classification	Wing Kam Liu; Zhengtao Gan; Mark Fleming	Mechanistic Data Science for STEM Education and Applications	Wing Kam Liu; Zhengtao Gan; Mark Fleming	1st ed. 2021	Springer International Publishing
Supervised learning strategies - regression versus classification		Machine Learning for Developers	Rodolfo Bonnin	0	Packt Publishing - ebooks Account
Supervised learning strategies - regression versus classification		Machine learning for developers: uplift your regular applications with the power of statistics, analytics, and machine learning	Bonnin, Rodolfo	2017	Packt Publishing - ebooks Account
Supervised learning â€“ classification and regression		Python: Data Analytics and Visualization	Phuong Vo.T.H, Martin Czygan, Ashish Kumar, Kirthi Raman	2017	Packt Publishing
Supervised learning â€“ classification and regression		Python: End-to-end Data Analysis: Leverage the Power of Python to Clean, Scrape, Analyze, and Visualize Your Data: a Course in Three Modules	Phuong Vo. T. H; Phuong Vothihong	2016
Supervised Learning—Classification Using Logistic Regression		Python Machine Learning	Wei-Meng Lee	2019	John Wiley & Sons
Classification = Regression		From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science	Norm Matloff	2013
Learning from Learning Theory	Alan Bleakley; John Bligh; Julie Browne	Medical Education for the Future: Identity, Power and Location	Alan Bleakley; John Bligh; Julie Browne	2011	Springer Netherlands
Pattern Classification and Learning Theory	G. Lugosi	Principles of Nonparametric Learning	Laszlo Györfi	2002	Springer Vienna
Introduction to machine learning: Regression, classification, and important concepts	Peter Mccaffrey	An Introduction to Healthcare Informatics	Peter Mccaffrey	2020	Academic Press
9. From errors theory to linear regression	Claude Meidinger	Uncertainty in economic thought /	Schmidt, Christian,	[1996], ©1996.	E. Elgar,
Learning to Speak Regression		Getting started with data science: making sense of data with analytics	Murtaza Haider	2016
From practice to theory: learning from conscience.		Catholic moral philosophy: in practice and theory: an introduction /	Prusak, Bernard G.		Paulist Press
Chapter	Author(s)	Book	Book Authors	Year	Publisher

Showing 1 to 20 of 100 entries

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