Isbn: 9783031318047 - machine learning governance for managers (17 resultados)

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Condición: New. 1st ed. 2024 edition NO-PA16APR2015-KAP.

Paperback. Condición: Brand New. 127 pages. 9.25x6.10x0.28 inches. In Stock.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment,performance measurement,and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices.Particular emphasis is given toramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance.Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized.Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide.…

Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment, performance measurement, and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices. Particular emphasis is given to ramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance.Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized.Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide.…

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment,performance measurement,and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices.Particular emphasis is given toramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance.Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized.Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide. 128 pp. Englisch.…

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Condición: New. PRINT ON DEMAND.

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Helps data science managers to scale and become more data- and AI-drivenHelps break through the complexity and challenges of moving data science and machine learning projects to productionHelps organizations improve results from their data .…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Machine Learning Governance for Managers provides readers with the knowledge to unlock insights from data and leverage AI solutions. In today's business landscape, most organizations face challenges in scaling and maintaining a sustainable machine learning model lifecycle. This book offers a comprehensive framework that covers business requirements, data generation and acquisition, modeling, model deployment, performance measurement, and management, providing a range of methodologies, technologies, and resources to assist data science managers in adopting data and AI-driven practices. Particular emphasis is given to ramping up a solution quickly, detailing skills and techniques to ensure the right things are measured and acted upon for reliable results and high performance.Readers will learn sustainable tools for implementing machine learning with existing IT and privacy policies, including versioning all models, creating documentation, monitoring models and their results, and assessing their causal business impact. By overcoming these challenges, bottom-line gains from AI investments can be realized.Organizations that implement all aspects of AI/ML model governance can achieve a high level of control and visibility over how models perform in production, leading to improved operational efficiency and a higher ROI on AI investments. Machine Learning Governance for Managers helps to effectively control model inputs and understand all the variables that may impact your results. Don't let challenges in machine learning hinder your organization's growth - unlock its potential with this essential guide.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 128 pp. Englisch.…