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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 ... -
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 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 ... -
A Beginner’s Guide to R
(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 ... -
Machine Learning in Medicine - A Complete Overview
(Springer, 2015)The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion, and as a must-read, not only for physicians and ... -
Linear Programming: Foundations and Extensions (4 ed.)
(Springer, 2014)This Fourth Edition introduces the latest theory and applications in optimization. It emphasizes constrained optimization, beginning with a substantial treatment of linear programming and then proceeding to convex analysis, ... -
The Data Science Design Manual
(Springer, 2017)This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data ... -
Statistical Analysis and Data Display: An Intermediate Course with Examples in R (2 ed.)
(Springer, 2015)This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, ... -
Computational Geometry: Algorithms and Applications (3 ed.)
(Springer, 2008)Computational geometry emerged from the ?eld of algorithms design and analysis in the late 1970s. It has grown into a recognized discipline with its own journals, conferences, and a large community of active researchers. ... -
Computer Vision: Algorithms and Applications
(Springer, 2011)Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level ... -
The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2 ed.)
(Springer, 2009)During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge ... -
MISR Advancing Artificial Intelligence Through Biological Process Applications
(IGI Global, 2008)"This book presents recent advancements in the study of certain biological processes related to information processing that are applied to artifcial intelligence. Describing the benefts of recently discovered and existing ... -
Artificial Neural Networks in Vehicular Pollution Modelling
(Springer, 2006)Artificial neural networks (ANNs), which are parallel computational models, comprising of interconnected adaptive processing units (neurons) have the capability to predict accurately the dispersive behavior of vehicular ... -
Applications of Data Mining in E-Business and Finance
(IOS Press, 2008)This book contains extended versions of a selection of papers from that workshop. Due to the importance of the two application areas, we have selected papers that are mostly related to finance and e-business. The chapters ... -
Encyclopedia of Artificial Intelligence
(Information Science Reference, 2009)'This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others''. -
Machine Learning and Data Mining in Pattern Recognition: Third International Conference, MLDM, Leipzig, Germany, July 25 5-7,, Proceedings
(Springer, 2003)The 33 papers in these proceedings cover a wide variety of topics related to machine learning and data mining. The two invited talks deal with learning in case-based reasoning and with mining for structural data. The ... -
MICAI 2007: Advances in Artificial Intelligence: 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007. Proceedings
(Springer-Verlag Berlin Heidelberg, 2007)Artificial Intelligence is a branch of computer science that studies heuristic methods of solving complex problems. Historically the first such tasks modeled human intellectual activity: reasoning, learning, seeing and ...
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