Now showing items 21-40 of 6633

    • Statistics and Analysis of Scientific Data (2 ed.) 

      Bonamente, Massimiliano (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.) 

      Brockwell, Peter J.; Davis, Richard A. (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.) 

      Dineen, Seán (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.) 

      Brandt, Siegmund (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.) 

      Bramer, Max (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 

      Lee, Kent D.; Hubbard, Steve (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.) 

      Angeles, Jorge (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 ...
    • Linear and Nonlinear Programming (4 ed.) 

      Luenberger, David G.; Ye, Yinyu (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 ...
    • Introduction to Partial Differential Equations 

      Borthwick, David (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 ...
    • Excel Data Analysis: Modeling and Simulation (2 ed.) 

      Guerrero, Hector (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.) 

      Eiben, A.E.; Smith, J.E. (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 

      Aggarwal, Charu C. (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.) 

      Ertel, Wolfgang (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 

      Skansi, Sandro (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 ...
    • A Beginner’s Guide to R 

      Zuur, Alain F.; Leno, Elena N.; Meesters, Erik H. W. G. (Springer, 2009)
      Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical ...
    • Foundations of Programming Languages (2 ed.) 

      Lee, Kent D. (Springer, 2017)
      This clearly written textbook provides an accessible introduction to the three programming paradigms of object-oriented/imperative, functional, and logic programming. Highly interactive in style, the text encourages learning ...
    • Bayesian Essentials with R (2 ed.) 

      Marin, Jean-Michel; Robert, Christian P. (Springer, 2014)
      This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called ...
    • Concise Guide to Databases: A Practical Introduction 

      Lake, Peter; Crowther, Paul (Springer, 2013)
      Modern businesses depend on data for their very survival, creating a need for sophisticated databases and database technologies to help store, organise and transport their valuable data. This easy-to-read textbook/reference ...
    • Digital Image Processing: An Algorithmic Introduction Using Java (2 ed.) 

      Burger, Wilhelm; Burge, Mark J. (Springer, 2016)
      This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with ...
    • Applied Predictive Modeling 

      Kuhn, Max; Johnson, Kjell (Springer, 2013)
      This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an ...