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Business and technical leaders will discover how to measure their organization's data science maturity and determine whether it is data-driven. They will also learn how to apply the Healthy Data Science Organization Framework to foster a healthy data science attitude within the organization through practical and applied use cases. This framework was developed based on my experience as a data scientist working on end-to-end machine learning and data science solutions with external customers from a variety of industries, including energy, oil and gas, retail, aerospace, healthcare, and…mehr

Produktbeschreibung
Business and technical leaders will discover how to measure their organization's data science maturity and determine whether it is data-driven. They will also learn how to apply the Healthy Data Science Organization Framework to foster a healthy data science attitude within the organization through practical and applied use cases. This framework was developed based on my experience as a data scientist working on end-to-end machine learning and data science solutions with external customers from a variety of industries, including energy, oil and gas, retail, aerospace, healthcare, and professional services. The framework offers a lifecycle to help you organize how your data science projects are developed. A project's lifespan illustrates what happens from beginning to end when it is completed.
Autorenporträt
Dr.Preethi. N é Professor Associado em Cristo (Deemed to be University) , campus de Lavasa, Pune. Os seus interesses de investigação são a aprendizagem de máquinas, aprendizagem profunda, etc.A Dra. (Fr) Jossy P George tem trabalhado com a Universidade de Cristo, Bengaluru, e actualmente é Directora e Reitora no Campus de Pune Lavasa, com dupla licenciatura dos EUA.