Machine Learning Applications In Software Engineering

This book constitutes the refereed proceedings of the 12th International Conference on Software Engineering and Formal Methods, SEFM 2014, held in Grenoble, France, in September 2014.The 23 full paper

This book constitutes the refereed proceedings of the 6th International Symposium on Engineering Secure Software and Systems, ESSoS 2014, held in Munich, Germany, in February 2014. The 11 full papers

This book constitutes the thoroughly refereed post-proceedings of the 4th International Conference on Software Language Engineering, SLE 2011, held in Braga, Portugal, in July 2011. The 18 papers pres

This book constitutes the refereed proceedings of the 9th International Symposium on Engineering Secure Software and Systems, ESSoS 2017, held in Bonn, Germany in July 2017. The 12 full papers

This book constitutes the refereed proceedings of the 7th International Symposium on Engineering Secure Software and Systems, ESSoS 2015, held in Milan, Italy, in March 2015. The 11 full papers presen

This book constitutes the refereed proceedings of the Fourth International Symposium on Search-Based Software Engineering, SSBSE 2012, held in Riva del Garda, Italy in collocation with the 28th IEEE I

This volume contains the lecture notes of the courses given at the School on Engineering Trustworthy Software Systems (SETSS 2014), held in the week 8{13 September 2014 at Southwest University in Chon

Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures.Key features: Demonstrates a quick review on Python, NumPy, and TensorFlow fundamentals.Explains and provides examples of deploying TensorFlow and Keras in several projects.Explains the fundamentals of Artificial Neural Networks (ANNs).Presents several examples and applications of ANNs.Learning the most popular DL algorithms features.Explains and provides examples for the DL algorithms that are presented in this book.Analyzes the DL network's parameter and hyperparameters.Reviews state-of-the-art DL examples.Necessary and main steps for DL modeling.Implements a Virtual Assistant Robot (VAR) using DL methods.Necessary and fundamental information to choose a proper DL algorithm.Gives instructions to learn how to optimize your DL model IN PRACTICE.This book is useful for undergraduate and graduate students, as well as practitioners in industry

This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about scientific questions, and leads readers through the history of the field and its fundamental connections to neuroscience. The author discusses many applications to beautiful problems in the natural sciences, in physics, chemistry, and biomedicine. Examples include the search for exotic particles and dark matter in experimental physics, the prediction of molecular properties and reaction outcomes in chemistry, and the prediction of protein structures and the diagnostic analysis of biomedical images in the natural sciences. The text is accompanied by a full set of exercises at different difficulty levels and encourages out-of-the-box thinking.

Technology-Enhanced Language Learning for Specialized Domains provides an exploration of the latest developments in technology-enhanced learning and the processing of languages for specific purposes.

This book provides an exploration of the latest developments in technology-enhanced learning and the processing of languages for specific purposes. Combining theoretical and applied research from an i

This edited volume brings together perspectives that find mutual kinship in a view of language as an embodied, semiotic, symbolic tool used for communicative and interactional purposes and an understa

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk a

This 2004 book is an accessible and comprehensive introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. The authors begin with a review of mathematical principles and go on to discuss key issues in image processing such as the description and characterization of images, edge detection, restoration and feature extraction, segmentation, texture and shape. They also discuss image matching, statistical pattern recognition, clustering, and syntactic pattern recognition. Important applications are described, including optical character recognition and automatic target recognition. Software and data used in the book can be found at www.cambridge.org/9780521830461. A useful reference for practitioners, the book is aimed at graduate students in

Frontiers in Education: Computer Science and Computer Engineering is a compendium of articles and papers that were presented at FECS '15, an international conference that serves researchers, scholars,

This book covers all aspects of operational modal analysis for civil engineering, from theoretical background to applications, including measurement hardware, software development, and data processing

This 2-Volume-Set, CCIS 0269-CCIS 0270, constitutes the refereed proceedings of the International Conference on Global Trends in Computing and Communication (CCIS 0269) and the International Conferenc

This is a comprehensive book for quick reference and review of metallurgical topics in an objective type questionswer format. Contains over 6,000 questions with answers.FeaturesCan be used as a rev

Zill presents readers with the sixth edition of his comprehensive guide to the mathematical concepts and equations involved in engineering. He has organized the twenty chapters that make up the main b

Books on engineering design, like designs them- selves, are highly individual. In this one, the author emphasizes the importance of a visual approach to machine design and makes his point by including

Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can b