English resources: Recent submissions
Now showing items 341-360 of 6959
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Statistical Learning from a Regression Perspective (2 ed.)
(Springer, 2016)This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors ... -
Understanding Statistics Using R
(Springer, 2013)This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The chapter content is ordered along the lines of many popular statistics books so it should ... -
An Introduction to Statistical Learning: with Applications in R
(Springer, 2013)An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from ... -
Linear Algebra
(Springer, 2015)This self-contained textbook takes a matrix-oriented approach to linear algebra and presents a complete theory, including all details and proofs, culminating in the Jordan canonical form and its proof. Throughout the ... -
Linear Algebra Done Right (3 ed.)
(Springer, 2015)This best-selling textbook for a second course in linear algebra is aimed at undergrad math majors and graduate students. The novel approach taken here banishes determinants to the end of the book. The text focuses on the ... -
Understanding Analysis (2 ed.)
(Springer, 2015)This lively introductory text exposes the student to the rewards of a rigorous study of functions of a real variable. In each chapter, informal discussions of questions that give analysis its inherent fascination are ... -
Statistics and Analysis of Scientific Data (2 ed.)
(Springer, 2017)The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of ... -
Introduction to Time Series and Forecasting (3 ed.)
(Springer, 2016)This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic ... -
Multivariate Calculus and Geometry (3 ed.)
(Springer, 2014)Multivariate calculus can be understood best by combining geometric insight, intuitive arguments, detailed explanations and mathematical reasoning. This textbook has successfully followed this programme. It additionally ... -
Data Analysis: Statistical and Computational Methods for Scientists and Engineers (4ed.)
(Springer, 2014)The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory ... -
Principles of Data Mining (3 ed.)
(Springer, 2016)This book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other ... -
Data Structures and Algorithms with Python
(Springer, 2015)This clearly structured and easy to read textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents ... -
Fundamentals of Robotic Mechanical Systems: Theory, Methods, and Algorithms (4 ed.)
(Springer, 2014)The 4th edition includes updated and additional examples and exercises on the core fundamental concepts of mechanics, robots, and kinematics of serial robots. New images of CAD models and physical robots help to motivate ... -
Introduction to Partial Differential Equations
(Springer, 2016)This modern take on partial differential equations does not require knowledge beyond vector calculus and linear algebra. The author focuses on the most important classical partial differential equations, including conservation ... -
Linear and Nonlinear Programming (4 ed.)
(Springer, 2016)This new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. Again a connection between the purely analytical character of an ... -
Excel Data Analysis: Modeling and Simulation (2 ed.)
(Springer, 2019)This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are ... -
Introduction to Evolutionary Computing (2 ed.)
(Springer, 2015)The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized ... -
Neural Networks and Deep Learning: A Textbook
(Springer, 2018)This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special ... -
Introduction to Artificial Intelligence (2 ed.)
(Springer, 2017)This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical ... -
Introduction to Deep Learning: From Logical Calculus to Artificial Intelligence
(Springer, 2018)This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular ...
