Machine Learning Applications In Software Engineering

This book presents and discusses the state of the art and future trends in software engineering education. It introduces new and innovative methods, models and frameworks to focus the training towards

A solid introduction to mathematical modeling for a range of chemical engineering applications, covering model formulation, simplification and validation. It explains how to describe a physical/chemical reality in mathematical language and how to select the type and degree of sophistication for a model. Model reduction and approximation methods are presented, including dimensional analysis, time constant analysis and asymptotic methods. An overview of solution methods for typical classes of models is given. As final steps in model building, parameter estimation and model validation and assessment are discussed. The reader is given hands-on experience of formulating new models, reducing the models and validating the models. The authors assume the knowledge of basic chemical engineering, in particular transport phenomena, as well as basic mathematics, statistics and programming. The accompanying problems, tutorials, and projects include model formulation at different levels, analysis, pa

This book describes new theories and applications of artificial neural networks, with a special focus on neural computation, cognitive science and machine learning. It discusses cutting-edge research

This tutorial book presents an augmented selection of the material presented at the International Summer School on Generative and Transformational Techniques in Software Engineering, GTTSE 2007, held

This book constitutes the refereed proceedings of the 11th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2015, held in Melbourne, Australia, in March 2015. The 62 revis

This book includes chapters based on the potential uses of polysaccharides such as fibers in food and non-food applications. The complexity of their synthesis in plants, the highly multidisciplinary c

The programming landscape of natural language processing has changed dramatically in the past few years. Machine learning approaches now require mature tools like Python’s scikit-learn to apply

This textbook is aimed at newcomers to nonlinear dynamics and chaos, especially students taking a first course in the subject. The presentation stresses analytical methods, concrete examples and geome

Steven H. Strogatz’s Nonlinear Dynamics and Chaos, second edition, is aimed at newcomers to nonlinear dynamics and chaos, especially students taking a first course in the subject. The presentation str

This book covers computer aided design (CAD), 3-D modeling and engineering analysis and ways they can be applied in research and industry including aerospace, defense, automotive and consumer products

This succinct book focuses on computer aided design (CAD), 3-D modeling, and engineering analysis and the ways they can be applied effectively in research and industrial sectors including aerospace, d

The core of ths book presents a theory developed by the author to combine the recent insight into empirical data with mathematical models in freeway traffic research based on dynamical non-linear proc

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.

Statistics, Data Mining, and Machine Learning in Astronomy is the essential introduction to the statistical methods needed to analyze complex data sets from astronomical surveys such as the Panoramic

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements f

This volume identifies promising learning, teaching, and assessment strategies for the use and assessment of technology in educational settings, specifically:*educational context (e.g., organizational

This book fills the need for a comprehensive volume on the most recent research on oscillator circuit design, analysis and application. It highlights developments in the analysis of synchronization an

Intended as a textbook for undergraduate courses in heat transfer for students of mechanical, chemical, aeronautical, and metallurgical engineering, or as a reference for professionals in industry, t

Provide your mechanical engineering students with a solid understanding of statics without the overload of extraneous detail in Andrew Pytel and Jaan Kiusalaas' ENGINEERING MECHANICS: STATICS, 4E. The