Comprehensive Project Management Framework using Machine Learning
Kalli Srinivasa Nageswara Prasad1, M. V. Vijaya Saradhi2

1Dr. Kalli Srinivasa Nageswara Prasad, Professor, Department of CSE, Ramachandra College of Engineering, Eluru (Andhra Pradesh), India.
2Dr. M. V. Vijaya Saradhi, Professor, Department of CSE, ACE Engineering College, Ghatkesar, Hyderabad (Telangana), India.
Manuscript received on 24 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 1373-1377 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B12560782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1256.0782S319
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Abstract: Among the key reasons for the project management failures, unrealistic project schedules and ineffective utilization of the project conditions are key challenges. Irrespective of the size of the project and nature of project, there is imperative need for ensuring project conditions are effectively planned and there is holistic structure in place for managing the projects. There are many online solutions too which provides significant insights in to the system and its practices. The emergence of AI and the machine learning models has created a paradigm shift in the way things are managed in the business and project functions. The decision-making related insights generated by the machine learning models can be a phenomenal impact for the organizations. It is evident from the depth of the study discussed in the report, that if effectively planned and right kind of machine learning models are chosen, there are prospective conditions for the models to be trained and an automated system be developed which can yield considerable results. Even for the implementation team, if there are too many ML models to be implemented as a process of detecting the right fit solutions and this study identifies the need for a more comprehensive and single-window system of machine learning based project management framework.
Keywords: ML based Project, AI based Project Management, AI based System Engineering, Sentimental Analysis based Project Models.
Scope of the Article: Machine Learning