So you're working on building a machine learning model, and you have hit the realization that you will need to annotate a lot of data to build a performant model. In the machine learning meta today, you will be bombarded with services offering to fully outsource your labeling woes.
When we are teaching a machine learning model to recognize items of interest, we often take a laser focus towards gathering a dataset that is representative of the task we want our algorithm to master.
Computer vision problems start with finding high quality image datasets. Fortunately, access to common image data is increasingly easier. Datasets like Microsoft's COCO dataset and the Pascal VOC dataset provide
At Roboflow, we often get asked, what is the train, validation, test split and why do I need it? The motivation is quite simple: you should separate you data into train, validation, and test splits to prevent your model from overfitting and to accurately evaluate your model.
As global coronavirus case numbers continue to climb, troubling stories of hospital shortages, deaths, and disrupted communities fill the news. Frankly, it can leave one feeling disempowered – especially when the