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How to Identify Use Cases For Machine Learning

How to Identify Use Cases For Machine Learning


Arnab Biswas

August 01, 2020


  1. Identifying Use Cases For Machine Learning Arnab Biswas arnabbiswas1

  2. • Identify your organization’s “X” most important strategic goals •

    What problems are you facing in achieving those goals? • Would those be good problems for ML?
  3. Sources To Identify Problems Good For ML • Manual Data

    Analysis Process • Rule based decision/prediction making using software Ref:
  4. Manual Data Analysis • Enlist the processes which need your

    team to spend lot of time on data analysis • For each process • Is this process of analyzing data highly repetitive? • Do you need to scale this process to achieve our strategic goals? • Do we have relevant data for that? Note : Higher volume processes are preferred Ref:
  5. Software decision-making • List all software processes that repeatedly makes

    a decision or a prediction based on a set of rules • Even excel or simple scripts should be considered as software • Are there too many rules? • Are the rules too complex? • Could a human expert make a better decision than the software? Note : Higher volume processes are preferred Ref:
  6. Types of data • Tabular Data (Information from Assets, Maintenance

    Records, Tickets) • Image (Photos, Maps, Videos) • Language (Details of a ticket, Customer Chat) • Audio (Recorded Calls)
  7. Validate Use cases

  8. Evaluate Use Cases High Risk High Effort Value Low Risk

    Low Effort Big bubbles at this corner are preferred Ref:
  9. Evaluation Criteria • Value • Value of the knowledge gained

    by solving the use case using ML • Effort • Order of magnitude of the problem • Risk • Is the data predictive enough? • Is the volume of data sufficient? • Is the technique time tasted?
  10. References • • usecase-checklist • •

    • time-and-get-more-done-e1f003e1c5ee