Would you like to understand the most important elements of Class diagrams? (See page 35.) Do you want to see …
For all developers who create models using the Unified Modeling Language (UML) 2.x The Elements of UML(TM) 2.0 Style sets …
This User Guide is a book that provides in-depth coverage of the language. It is not a book on Object …
Since its original introduction in 1997, the Unified Modeling Language has revolutionized software development. Every integrated software development environment in …
Data Modeling Essentials, Third Edition provides expert tutelage for data modelers, business analysts and systems designers at all levels. Beginning …
Logical Data Modeling offers business managers, analysts, and students a clear, basic systematic guide to defining business information structures in …
Although AI has incredible potential, it has three weak links: 1. Blackbox, lack of explainability2. Silos, slews of siloed systems …
The Sixth Edition of this very successful textbook, Introduction to Probability Models<$>, introduces elementary probability theory and stochastic processes. This …
It's a great over view of UML and design practices. This book is what it says it is, an introduction …
The Elements of UML Style is for all developers who create models using the Unified Modeling Language (UML), especially those …
If you are in the game business you must have this book and read it ofcourse :)
R has been the gold standard in applied machine learning for a long time. Surveys show that it is the …
Got this book to prepare for my interview. It is a nice book that covers all the topics. It's not …
Brain Dynamics serves to introduce graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. …
Modern Applications of Graph Theory discusses many cutting-edge applications of graph theory, such as traffic networks, navigable networks and optimal …
Computers are one of the most important tools available to physicists, whether for calculating and displaying results, simulating experiments, or …
Computational physics is a rapidly growing subfield of computational science, in large part because computers can solve previously intractable problems …
The increased efficiency and quality constraints imposed on electrical energy systems have inspired a renewed research interest in the study …
The book explicates with several examples the part related to "evolution" of the game theory. This aspect is very important …
This book introduces one of the most powerful tools of modern economics to a wide audience: those who will later …
This book provides a clear picture of the use of applied mathematics as a tool for improving the accuracy of …
This book provides a comprehensive introduction to actuarial mathematics, covering both deterministic and stochastic models of life contingencies, as well …
A fascinating consideration of the work of life models and the models' own perspectives on their craft.
Modelling in Transport Phenomena, Second Edition presents and clearly explains with example problems the basic concepts and their applications to …
The practice of low-speed experimental aerodynamics has continued to evolve and continues to be a cornerstone in the development for …
This volume consists of papers written by eminent scientists from the international mathematical community, who present the recent research concerning …
Computational Fluid-Structure Interaction: Methods, Models, and Applications provides detailed explanations of a range of FSI models, their mathematical formulations, validations, …
Drawing on the authors’ two decades of experience in applied modeling and data mining, Foundations of Predictive Analytics presents the …
"Utility-Based Learning from Data is an excellent treatment of data-driven statistics for decision-making. Friedman and Sandow lucidly describe the connections …
Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for …
This textbook presents methods and techniques for time series analysis and forecasting and shows how to use Python to implement …
