How To Generate Quality Training Data For Your Machine Learning Projects

Have you run into issues acquiring the right type of data for your machine learning (ML) projects?

You’re not alone. Many teams do. And data is one of the key sticking points in starting AI initiatives at companies. In fact, according to IBM’s CEO, Arvind Krishna, data-related challenges are the top reason IBM clients have halted or canceled AI projects. 

Often what happens in practice is that the relevant ML training data is either not collected, or collected but the data lacks the required labels for training a model. It could also be that the existing volume of data is insufficient for ML

 

 

 

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