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Your AI and ML Projects Are Failing – Key Steps to Get Them Back on Track
Tuesday 22 October 2019, 17:00 - 18:00
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With recent studies indicating that 80% of AI and machine learning projects are failing due to data quality related issues, it’s critical to think holistically about this fact. This is not a simple topic – issues in data quality can occur throughout from starting the project through to model implementation and usage.

In this Syncsort webinar, we start with four foundational data steps to get our AI and ML projects grounded and underway, specifically:

  • framing the business problem
  • identifying the “right” data to collect and work with
  • establishing baselines of data quality through data profiling and business rules
  • assessing fitness for purpose for training and evaluating the subsequent models and algorithms

Register here

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