(Izdošanas datums: 24-Dec-2024, PDF+DRM, Izdevniecība: MIT Press Ltd, ISBN-13: 9780262381376)
A comprehensive and cutting-edge introduction to the foundations and modern applications of learning theory.Research has exploded in the field of machine learning resulting in complex mathematical arguments that are hard to grasp for new comers. In t...Lasīt vairāk
Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller
(Izdošanas datums: 16-Aug-2024, PDF+DRM, Izdevniecība: Taylor & Francis Ltd, ISBN-13: 9780429679537)
Symbolic regression (SR) is one of the most powerful machine learning techniques that produces transparent models, searching the space of mathematical expressions for a model that represents the relationship between the predictors and the dependent v...Lasīt vairāk
Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, Michael Affenzeller
(Izdošanas datums: 16-Aug-2024, EPUB+DRM, Izdevniecība: Taylor & Francis Ltd, ISBN-13: 9780429679421)
Symbolic regression (SR) is one of the most powerful machine learning techniques that produces transparent models, searching the space of mathematical expressions for a model that represents the relationship between the predictors and the dependent v...Lasīt vairāk
The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers an...Lasīt vairāk
The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers an...Lasīt vairāk
(Izdošanas datums: 31-Aug-2023, PDF+DRM, Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, ISBN-13: 9783662678824)
This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of data science. It covers essential parts of data organization, descriptive and inferential statistics, probability theory, and m...Lasīt vairāk
(Izdošanas datums: 09-May-2023, PDF+DRM, Izdevniecība: Taylor & Francis Ltd, ISBN-13: 9781000856163)
This book takes a deep dive into several key linear algebra subjects as they apply to data analytics and data mining. The book offers a case study approach where each case will be grounded in a real-world application. This text is meant to be used fo...Lasīt vairāk
(Izdošanas datums: 09-May-2023, EPUB+DRM, Izdevniecība: Taylor & Francis Ltd, ISBN-13: 9781000856200)
This book takes a deep dive into several key linear algebra subjects as they apply to data analytics and data mining. The book offers a case study approach where each case will be grounded in a real-world application. This text is meant to be used fo...Lasīt vairāk
(Izdošanas datums: 05-Apr-2023, EPUB+DRM, Izdevniecība: Taylor & Francis Ltd, ISBN-13: 9781000863017)
torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++.Though still "e;young"e; as a...Lasīt vairāk
(Izdošanas datums: 05-Apr-2023, PDF+DRM, Izdevniecība: Taylor & Francis Ltd, ISBN-13: 9781000862935)
torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++.Though still "e;young"e; as a...Lasīt vairāk
Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical is...Lasīt vairāk
Hamiltonian Monte Carlo Methods in Machine Learning introduces methods for optimal tuning of HMC parameters, along with an introduction of Shadow and Non-canonical HMC methods with improvements and speedup. Lastly, the authors address the critical is...Lasīt vairāk
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of line...Lasīt vairāk
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of line...Lasīt vairāk
This book focuses on adaptive iterative learning control problem for nonlinear time-delay systems.A universal adaptive learning control scheme is provided for a wide classes of nonlinear systems with time-varying delay and input nonlinearity. Proceed...Lasīt vairāk
This book focuses on adaptive iterative learning control problem for nonlinear time-delay systems.A universal adaptive learning control scheme is provided for a wide classes of nonlinear systems with time-varying delay and input nonlinearity. Proceed...Lasīt vairāk
