Capstone – Project

Machine Learning Technology Evaluation & Testing

A Collaboration Between

Project Synopsis

Students in the MSBA 790 will deliver the following:
  • 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.
  • 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 Topics

Data Management

Product Design & Development

Quality Control

Company Information

CompanyEco-Enterprise
HQNew Jersey
RevenueUnlisted
Employees1-5
StagePre-Revenue Startup
Hiring PotentialFollow-on Projects, Formal Internship, Entry Level Full-Time, Upper Level Full-Time
Websitehttp://Eco-Enterprise.com

Company Overview

eco-enterprise helps businesses to become more Efficient, Economic and Environmentally responsible via unique financial solutions and energy-saving technologies.

Experiential Learning Program Details

SchoolUniversity of South Carolina – Upstate
Engagement Format -
CourseSummer Capstone in Business Analytics
Level
  • All Graduate
Students Enrolled40
Meeting Day & TimeOnline
Student Time Commitment4-7 Hours Per Week
Company Time Commitment1 Hour
Duration8.29 Weeks

Program Timeline

Touchpoints & Assignments Due Date Type
REMINDER OF CONFIDENTIALITY

REMINDER OF CONFIDENTIALITY

During this program, you'll be working on a real project posed by a real industry partner. By registering for the CapSource system and participating in this Program, you are bound by the Rules of Engagement, including strict confidentiality of information shared with you. Please be respectful and professional.
June 4th, 2021 Event na
Complete Pre-Kickoff Evaluation

Complete Pre-Kickoff Evaluation

June 6th, 2021 Event na
OFFICIAL PROJECT KICKOFF

OFFICIAL PROJECT KICKOFF

Find time to web conference and discuss project goals and timeline
June 14th, 2021 Event na
Complete Temp Check Evaluation

Complete Temp Check Evaluation

June 28th, 2021 Event na
Complete Temp Check Evaluation

Complete Temp Check Evaluation

July 14th, 2021 Event na
OFFICIAL PROJECT END

OFFICIAL PROJECT END

August 4th, 2021 Event na
Complete Final Peer Evaluation Survey

Complete Final Peer Evaluation Survey

August 7th, 2021 Event na
Complete Final Self Evaluation Survey

Complete Final Self Evaluation Survey

August 7th, 2021 Event na

Key Project Milestones

  • June 18, 2021 - Define ML Problem to be Solved

    What is the ML Problem to be Solved given the data set and product goals of the Eco Enterprise IIOT platform?


    Suggested Deliverable:

    Learn more about HVAC system and define the ML problem to be solved

  • July 2, 2021 - Initial Evaluation of ML Tools

    • What are the top ML tools in the market?
    • How are they used? By whom?
    • How might Eco Enterprise be able to leverage different existing ML technology to glean relevant insights?

    Suggested Deliverable:

    Present top ML platform for consideration, how they’re used by similar companies for similar purposes, and initial pros/cons comparison of each

    Ensure you have access to sample data for next phase

  • August 4, 2021 - Recommend Top Choice Machine Language Technology

    Run the sample data through each of the machine learning technologies with the goal of identifying outliers and anomalies within the data set. Increase the quality of your pros and cons comparison analysis based on your experience running the data through the tool and developing insights.


    Suggested Deliverable:

    Produce a final report highlighting the top choice machine learning platform given your understanding of Eco Enterprise’s Machine Learning Problem to be solved, the sample data, and the outcomes of your pilot using the sample data.

    Which of the ML algorithmes presents the best framework for analyzing the data?

    What insights were you able to generate based on the sample data?

    How might this further improve as you add further data?

    What are the cost and benefit implications of choosing your selected tool? Why does that present a benefit over other choices?

Project Resources

There are no resources currently available

Industry Mentors

Company Admin

Lindsey Nagy

[email protected]

Company Admin

Nate Albee

[email protected]

Academic Mentors

There are currently no supervisors assigned.

Assigned Students

Student

Camilla Kilinc 

[email protected]