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Machine Learning for Managers

Machine Learning for Managers

Machine learning can help managers make better predictions automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about but who lack a technical background in computer science statistics or math. The book describes in plain language what machine learning is and how it works. In addition it explains how to manage machine learning projects within an organization. This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations. | Machine Learning for Managers

GBP 29.99
1

Machine Learning in Translation

Machine Learning in Translation

Machine Learning in Translation introduces machine learning (ML) theories and technologies that are most relevant to translation processes approaching the topic from a human perspective and emphasizing that ML and ML-driven technologies are tools for humans. Providing an exploration of the common ground between human and machine learning and of the nature of translation that leverages this new dimension this book helps linguists translators and localizers better find their added value in a ML-driven translation environment. Part One explores how humans and machines approach the problem of translation in their own particular ways in terms of word embeddings chunking of larger meaning units and prediction in translation based upon the broader context. Part Two introduces key tasks including machine translation translation quality assessment and quality estimation and other Natural Language Processing (NLP) tasks in translation. Part Three focuses on the role of data in both human and machine learning processes. It proposes that a translator’s unique value lies in the capability to create manage and leverage language data in different ML tasks in the translation process. It outlines new knowledge and skills that need to be incorporated into traditional translation education in the machine learning era. The book concludes with a discussion of human-centered machine learning in translation stressing the need to empower translators with ML knowledge through communication with ML users developers and programmers and with opportunities for continuous learning. This accessible guide is designed for current and future users of ML technologies in localization workflows including students on courses in translation and localization language technology and related areas. It supports the professional development of translation practitioners so that they can fully utilize ML technologies and design their own human-centered ML-driven translation workflows and NLP tasks.

GBP 34.99
1