Machine Learning Applications In Software Engineering

This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012.The

This is a book of stories based on companies in the Silicon Valley where people have been known to yell at each other. It is a place full of dysfunctional bright people who are in an incredible hurry

This book constitutes the thoroughly refereed post-conference proceedings of the Second IFIP TC 2 Central and East Conference on Software Engineering Techniques, CEE-SET 2007, held in Poznan, Poland,

Readers will be able to build and program their own 8088 single-board computer by applying the interfacing concepts and techniques presented in this book. Coverage begins with the software architect

The main subjects in this book relate to software development using cutting-edge technologies for real-world industrial automation applications A hands-on approach to applying a wide variety of emerg

The Handbook is written for academics, researchers, practitioners and advanced graduate students. It has been designed to be read by those new or starting out in the field of spatial analysis as well

Eisner (engineering and applied science, George Washington U.) explores the variety of systems that people are embedded in, and explains how to analyze and evaluate the ones that are inherited and des

This groundbreaking volume covers the significant advantages of wave technologies in the development of innovative machine building where high technologies with appreciable economic effect are applied

This book collects and reports on the results of a study conducted on the Chinese Software and Services Outsourcing (SSO) industry, focusing on one of its main players as a key case study. Two sets of

Accurate fluid level measurement in dynamic environments can be assessed using a Support Vector Machine (SVM) approach. SVM is a supervised learning model that analyzes and recognizes patterns. It is

Become proficient in deriving insights from time-series data and analyzing a model's performanceKey Features: Explore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time-series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description: Machine learning has emerged as a powerful tool to understand hidden complexities in time-series datasets, which frequently need to be analyzed in areas as diverse as healthcare, economics, digital marketing, and social sciences. These datasets are essential for forecasting and predicting outcomes or for detecting anomalies to support informed decision making.This book covers Python basics for time-series and builds your understanding of traditional autoregressive models as well as modern non-parametric models. You will become confident with

Autodesk Revit Architecture software provides building information modeling (BIM) data that allows you to design buildings with modeling and drafting elements. This book provides basic, step-by-step

The book is about a very active research field in software engineering. In modern society, the fact of the world's high reliance on software requires the system's robustness, i.e., continual availabil

Master the tools of MATLAB through hands-on examplesShows How to Solve Math Problems Using MATLABThe mathematical software MATLABR integrates computation, visualization, and programming to produce a p

This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems.

In Practical Machine Learning with H2O.ai, author Darren Cook introduces readers to H2O, an open-source machine learning package that is gaining popularity in the data science community. This concise