Is Your Business Ready for Machine Learning?


Are you ready to implement advanced machine learning solutions in your organization?

Your team’s ability to lower costs, increase efficiency, and achieve new breakthroughs will be shaped by its machine learning background, your data policies, and, most importantly, the actual data you’ll use.

Here are some questions to help you think through your machine learning readiness. At Infinia ML, we use a version of this survey before helping potential clients think through the possibilities. Before you work with us – or any machine learning expert – it’s helpful to know where your team is starting from.

Machine Learning Background

What is your biggest machine learning business need? Why do you think machine learning is the solution?

Have you implemented machine learning before? If so, what frameworks did you use (e.g., Tensorflow, PyTorch, etc.)? What was the result?

How many people on your team have machine learning ability at the following levels:

  • Beginner
  • Intermediate
  • Expert

What machine learning techniques most interest you?

  • Classification
  • Numeric Prediction
  • Natural Language Processing
  • Deep Learning
  • Image Recognition
  • Other
Data Policies

What tools or programming languages does your team use to query, manipulate, and report on data?

What are the job titles on the team that works with the data? (Business Analyst, Data Scientist, Software Engineer, etc.)

Do you use third-party or public data sets? If not, are you open to the idea?

What are your data governance processes?

Your Data

Who owns the data (your company, a third party, the public domain, etc.)?

What kind of data is it?

  • Numeric
  • Text
  • Images
  • Video
  • Other (please describe):

How quickly can your team access the data?

  • Immediately
  • Upon request
  • After getting approval
  • Don’t know

How often is your data updated?

How big is the data set?

Who manages the data?

How is the data stored (local MySQL, AWS S3, Hadoop, etc.)

How sensitive is the data?

Are you ready to talk about advanced machine learning? So are we. We look forward to hearing from you!

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