• Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
• Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
• Build models relating to neural...

This is the first book to show the capabilities of Microsoft Excel to teach human resource management statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical human resource management problems. If understanding statistics isn’t your strongest suit, you...

This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively.  It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems.  If understanding statistics isn’t your strongest suit, you...

This book is a detailed discussion of the Diesel Combustion phenomena like ignition delay, fuel air mixing, rate of heat release, and emissions of smoke, particulate and nitric oxide. The book enables quantitative evaluation of these important phenomena and parameters. Most importantly, it attempts to model them with constants that are...

Drawing on the author's over thirty years of expertise in compiler development, research, and instruction, Trustworthy Compilers introduces and analyzes the concept of trustworthy compilers and the principles...

This revised and extensively expanded edition of Computability and Complexity Theory comprises essential materials that are core knowledge in the theory of computation. The book is self-contained, with a preliminary chapter describing key mathematical concepts and notations.  Subsequent chapters move from the qualitative aspects of...