Machine Learning Applications In Software Engineering

This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the

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 onl

With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and jour

A large international conference on Advances in Machine Learning and Data Analysis was held in UC Berkeley, California, USA, October 22-24, 2008, under the auspices of the World Congress on Engineerin

The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and st

This book presents and discusses the state of the art and future trends in software engineering education, with a focus on agile methods and their budgetary implications. It introduces new and innovat

The underlying argument here is that software should be empirically tested both by researchers in laboratory contexts, and by practitioners in industrial contexts. Contributors from both realms in Eur

This book addresses engineering learning in early childhood, spanning ages 3 to 8 years. It explores why engineering experiences are important in young children's overall development and how engineeri

In a down-to-the earth manner, the volume lucidly presents how the fundamental concepts, methodology, and algorithms of Computational Intelligence are efficiently exploited in Software Engineering and

Software quality stems from two distinctive, but associated, topics in software engineering: software functional quality and software structural quality. Software Quality Engineering studies the tenet

Dorf (electrical and computer engineering, University of California-Davis) provides a reference to subjects in the fields of digital logic devices, displays, testing, software, and computers, covering

The art, craft, discipline, logic, practice, and science of developing large-scale software products needs a believable, professional base. The textbooks in this three-volume set combine informal, eng

PRINCIPLES AND PRACTICES OF SOFTWARE ENGINEERING is a comprehensive and detailed text in the area of Software Engineering. It includes topics on Software Quality, Software Testing and Metrics. There i

This book provides a progressive approach to the teaching of software engineering. It features over 70 easy-to-follow diagrams and tables depicting concepts and tools used in software engineering and

In machine learning applications, practitioners must take into account the cost associated with the algorithm. These costs include: Cost of acquiring training dataCost of data annotation/labeling and

This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering problems. With a consistent emphasis on the connections between estimation, detection, information theory, and optimization, it includes: an accessible overview of the relationships between machine learning and signal processing, providing a solid foundation for further study; clear explanations of the differences between state-of-the-art techniques and more classical methods, equipping students with all the understanding they need to make informed technique choices; demonstration of the links between information-theoretical concepts and their practical engineering relevance; reproducible examples using Matlab, enabling hands-on student experimentation. Assuming only a basic understanding of probability and linear algebra, and accompanied by lecture slide

ENGINEERING APPLICATIONS IN SUSTAINABLE DESIGN AND DEVELOPMENT is an invaluable resource for today's engineering student. Focusing on pressing contemporary issues, the text puts product design in the

This volume presents a comprehensive treatment of Riemannian geometry as a mathematical and computational framework for many problems in machine learning, statistics, optimization, and computer vision