Lazzeri, Francesca. creator author. aut http://id.loc.gov/vocabulary/relators/aut Robsky, Alexei. author. aut http://id.loc.gov/vocabulary/relators/aut SpringerLink (Online service) text sz 2024 1st ed. 2024. monographic eng

electronic

electronic resource

access XIX, 108 p. 17 illus. in color. online resource. 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, monitoringmodels 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. 1. Understanding Business Goals -- 2. Measure the Right Things -- 3. Searching for the Right Tools -- 4. MLOps Governance & Architecting the Data Science Solution -- 5. Unifying Organizations’ Machine Learning Vision. by Francesca Lazzeri, Alexei Robsky. Machine learning Engineering Data processing Artificial intelligence Data processing Business Data processing Mathematical statistics Data processing Machine Learning Data Engineering Data Science Business Analytics Statistics and Computing Q325.5-.7 9783031318054 https://doi.org/10.1007/978-3-031-31805-4 https://doi.org/10.1007/978-3-031-31805-4 231124 20251030110837.0 978-3-031-31805-4