ProgramsSummer Capstone in Business AnalyticsProjectsMachine Learning Technology Evaluation & Testing

Project Title: Machine Learning Technology Evaluation & Testing

Eco-Enterprise, Inc.

Details
Project Title Machine Learning Technology Evaluation & Testing
Project Topics Data Management Product Design & Development Quality Control
Skills & Expertise
Project Synopsis: Challenge/Opportunity
Students in the MSBA 790 will deliver the following:
Project Synopsis: Activities/Actions Required
  • Evaluate the top five to seven Machine Learning platforms for our Industrial Internet of Things (IIOT) platform. Our IIOT solution is a big data cloud application that captures 31,536,000 rows of data containing over 1.5B data points every year for each device deployed. Students must present the pros and cons of using different ML tools and frameworks to process Big Data and extract key insights. 
  • An ML problem that is of interest to us is the impact of outliers on energy costs and long-term implications on energy consumption. We will provide students with a large data set to solve this problem using ML algorithms. Students must review and identify the appropriate ML algorithms for this problem. These algorithms must be executed (run) on the above ML platforms. An evaluation of the performance of the different ML platforms using this data set must be included in the presentation and report.
  • Students must also divide the data set that we provide into testing and training data and provide a detailed explanation as to how this was done.
Project Synopsis: Expected Results
The above information should be included both in your presentation and a detailed written report. This includes the following:  a) Highlight the top choice ML platform given your understanding of Eco Enterprise's goals. b)Which of the ML algorithms presents the best framework for analyzing the data? c) What insights were you able to generate based on the sample data? d) How might these insights further improve as you add more data? What are the cost and benefit implications of ML, in general?

Project Timeline

Touchpoints & Assignments Date Type

REMINDER OF CONFIDENTIALITY

 Apr 06 2021

OFFICIAL PROJECT END

 Apr 08 2021

Complete Pre-Kickoff Evaluation

 Jun 06 2021

Program Kickoff

 Jun 07 2021 Event

Complete Final Peer Evaluation Survey

 Jul 08 2021

Complete Final Self Evaluation Survey

 Jul 08 2021

Complete Temp Check Evaluation

Complete Temp Check Evaluation

OFFICIAL PROJECT KICKOFF

Program Managers

Name Organization
Uma Gupta University of South Carolina - Upstate

Teams

Team Name  Project Name  Team Members 
No Teams Available