How to Properly Prepare Your Data for Supervised Learning

So, Your Company Has Decided To Invest In Supervised Machine Learning
Awesome! Now what?

We've created a short guide on how to properly implement supervised learning and why partnering with the right third party data labeling platform that understands both the art and (data) science of the process will provide the crucial support for ML model development and ultimate success.

We outline the 4 necessary steps to consider when implementing supervised learning: 

  1. Build a data strategy
  2. Define your data quality requirements 
  3. Establish a training data pipeline
  4. Select a data labeling solution 

How to Properly Prepare Your Data for Supervised Learning