More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized
Society, Culture and Politics in Byzantium is the fourth selection of papers by the late Nicolas Oikonomides to be published in the Variorum Collected Studies Series. Its focus is upon the Byzantine world after the Fourth Crusade and during the Palaeologan period, though several studies deal with a longer time span. The twenty-eight articles included look first at questions of language and literacy, and then at the relationships between art and politics. The final sections examine aspects of the history of the later empire, in the age of its decline, caught between the economic penetration of the Western European states and the expansion of the Ottoman Turks, and consider the development of Byzantine institutions, monasteries and the Church in this period.
As the use of AI becomes more and more ubiquitous in companies around the world, managers charged with taking key decisions require resources to enable them to evaluate new projects effectively. The business case for AI projects is not necessarily clear cut and part of the reason for this is the lack of understanding on key decision criteria. AI touches on many ethical concepts - data privacy, validity and more importantly, its potential misuse. AI is often being used to replace human decision-making and there is often no real understanding of the implications of this. This book provides a detailed primer for practitioners without a deep technological background. It guides the reader through the basic issues and offers advice on ‘how to take decisions’. There is a dearth of such books currently available and this book aspires to fill a growing niche. ENDORSEMENTS: "This book is sure to offer value to business users, students and the general public." — K. Ananth Krishnan, Tata Consultancy Services "I highly recommend this book for the leader seeking an up-to-date review of AI to make strategic investments." — Kes Sampanthar, Innovation, BCG Brighthouse "The specificity of application in case studies and easy to understand definitions and recommendations make this a must read in the ever-growing field of literature around AI." — John C. Havens "The AI Enabled Organization is the perfect tool to embark on a thorough assessment of what AI means for your business." — Arno Fehler, Schmidt Kranz Group, Germany
Social and Economic Life in Byzantium is the third selection of papers by the late Nicolas Oikonomides to be published in the Variorum Collected Studies Series; a fourth, Society, Culture and Politics in Byzantium, will follow in 2005. The present volume is centred upon the period from the 9th to the 11th century, and a series of examinations into the society and economic activity of the Byzantine world. Other groups of studies investigate relations between state and church, monasteries in particular, aspects of the history of the Slavs in the Balkans, and topics in Byzantine epigraphy.
This much-acclaimed work was first published in 1985 in an extremely limited edition of something under 200 copies. The first edition nonetheless sold out rapidly, and the reviewers were virtually universal in their recommendations that a new edition be published at a more accessible price, and thereby satisfy the additional demands on the marketplace. This new edition meets that need. This second edition is a substantially new work. It has been completely revised throughout, in the light both of the author's subsequent research and discoveries and of the reviewers' observations. It contains much additional new matter. The new illustrations reproduce setting copy, in the autograph of Marcus Musurus, of the Address to the Reader in the 1498 Aristophanes
More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized
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