Ebook > Ciencia > Matemáticas > Robert E. Burks & William P. Fox: Modeling Change and Uncertainty (PDF)

Robert E. Burks & William P. Fox
Modeling Change and Uncertainty
Machine Learning and Other Techniques

Soporte

Portada de Robert E. Burks & William P. Fox: Modeling Change and Uncertainty (PDF)

This book offers a problem-solving approach. The authors introduce a problem to help motivate the learning of a particular mathematical modeling topic. The problem provides the issue or what is needed to solve using an appropriate modeling technique.

€106.05

Idioma Inglés ● Formato PDF ● Páginas 464 ● ISBN 9781000603873 ● Editorial CRC Press ● Publicado 2022 ● Descargable 3 veces ● Divisa EUR ● ID 8410909 ● Protección de copia Adobe DRM

Requiere lector de ebook con capacidad DRM

Más ebooks del mismo autor / Editor

Robert E. Burks William P. Fox William P. (U. S. Naval Post Graduate School) Fox

47.429 Ebooks en esta categoría

Portada de COMAP: For All Practical Purposes

COMAP: For All Practical Purposes

Portada de Lucia Darrow & Walter DeGrange: Field Guide to Compelling Analytics

Lucia Darrow & Walter DeGrange: Field Guide to Compelling Analytics

Field Guide to Compelling Analytics is written for Analytics Professionals (APs) who want to increase their probability of success in implementing analytical solutions. In the past, soft skills such …

Portada de Michael J. (University of Florida, Gainesville, USA) Daniels & Antonio Linero: Bayesian Nonparametrics for Causal Inference and Missing Data

Michael J. (University of Florida, Gainesville, USA) Daniels & Antonio Linero: Bayesian Nonparametrics for Causal Inference and Missing Data

Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional rela …

Portada de Chris (University of Bath, UK) Chatfield: Problem Solving

Chris (University of Bath, UK) Chatfield: Problem Solving

This book illuminates the complex process of problem solving, including formulating the problem, collecting and analyzing data, and presenting the …

Portada de Rudolf Taschner: Numbers at Work

Rudolf Taschner: Numbers at Work

Drawing primarily from historical examples, this book explains the tremendous role that numbers and, in particular, mathematics play in all aspects of our civilization and culture. The lively style …

Portada de Martin Hugh (University of Victoria, Division of Continuing Studies, Canada) Monkman: The Data Preparation Journey

Martin Hugh (University of Victoria, Division of Continuing Studies, Canada) Monkman: The Data Preparation Journey

The Data Preparation Journey: Finding Your Way With R introduces the principles of data preparation within in a systematic approach that follows a typical data science or statistical workflow. With t …

Portada de H.R. Madala: Inductive Learning Algorithms for Complex Systems Modeling

H.R. Madala: Inductive Learning Algorithms for Complex Systems Modeling

Inductive Learning Algorithms for Complex Systems Modeling is a professional monograph that surveys new types of learning algorithms for modeling complex scientific systems in science and …

Portada de John E. Kolassa: An Introduction to Nonparametric Statistics

John E. Kolassa: An Introduction to Nonparametric Statistics

An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data.　Rank-based and resamplin …

Portada de William H. Beyer: Handbook of Mathematical Science

William H. Beyer: Handbook of Mathematical Science

Numerical tables of mathematical and statistical functions are in continual demand by professional scientists, by those in the teaching profession, and by students of mathematics and related …

Portada de Diana Cole: Parameter Redundancy and Identifiability

Diana Cole: Parameter Redundancy and Identifiability

siguiente página >>>