The purpose of this research is to understand the main managerial challenges that arise in the context of Machine Learning. This research aims to explore the core concepts of Machine Learning and provide the same conceptual foundation to managers to overcome possible obstacles while implementing Machine Learning. Therefore, the main research question is: What are the phases and the main challenges while managing Machine Learning project in a product based IT organization? The focus is on the main concepts of Machine Learning and identifying challenges during each phase through literature review and qualitative data collected from interviews conducted with professionals. The research aims to position itself in the field of research which looks for inputs from consultants and management professionals either associated with Machine Learning or they are planning to start such initiatives. In this research paper we introduce ACDDT (Agile-Customer-Data-Domain-Technology) model framework for managers. This framework is centered on the main challenges in Machine Learning project phases while dealing with customer, data, domain and technology. In addition, the frame work also provides key inputs to managers for managing those challenges and possibly overcome them.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-18835 |
| Date | January 2019 |
| Creators | Bangabash, Subhasish, Panda, Srimanta |
| Publisher | Blekinge Tekniska Högskola, Institutionen för industriell ekonomi, Blekinge Tekniska Högskola, Institutionen för industriell ekonomi |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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