Hardest Part Of AI Is Cleaning Up Your Data - Tips From Experts

As more tools become available to create AI models, it has become easier for companies to harness the power of machine learning for their applications. What once required deep domain expertise to execute has been made easier by libraries and frameworks, such as Google's TensorFlow. To be clear, none of it is'easy,' but it may well be that the hardest part of the AI equation is acquiring, wrangling and, perhaps most poignantly, cleaning the data required to do the job. Engineers without experience in AI may well underestimate the time and effort required to get data to a point where AI will make the greatest impact, where the model will be as powerful and predictive as it can be. We talked to many data scientists and engineers who estimated that, on a given AI project, corralling, moving (these datasets can be unwieldy in their size), checking and organizing the data often comprises 70% to 80% of the time spent on a project.