Outsourcing data annotation involves hiring a third-party company to annotate data on behalf of the ML company. This can save a lot of time and effort for ML companies, as they can focus on their core competencies while the annotation work is done by the outsourcing partner. Outsourcing data annotation has many benefits, including increased
Data annotation is crucial for retail businesses, but it comes with its own set of challenges. From determining the right annotation method to managing large data sets, retailers are often faced with various obstacles. Springbord has compiled a list of the most frequently asked data annotation challenges for retail and offers expert solutions to overcome
Putting together useful training datasets requires a procedure known as “data annotation,” which entails classifying and labeling data. Training datasets are only useful if they have been properly organized and annotated for their intended purpose. Annotating data may seem like a mindless, repetitive task that takes no planning or forethought. Annotators need only prepare and