by Team Diffgram | Apr 7, 2022 | Training Data 101
The quality of your Training Data is defined by the quality of annotations and labels. Your annotators can label your training data with the tools you (or your data labeling software vendor) provide them. The right instance type will help you label easily and...
by Team Diffgram | Apr 5, 2022 | Training Data 101
What is Image Annotation? Image annotation is the process of annotating or labeling images in a given dataset. These data sets are used to train an ML model. By annotating images, you add labels to the features of the images that you expect your ML algorithm to...
by Team Diffgram | Mar 30, 2022 | Updates
After examining ten of the frequently cited datasets for testing machine learning systems, MIT Computer researchers have found out that these data sets have critical labeling errors. These errors could cause deep problems for AI systems developed using them. The...
by Team Diffgram | Feb 22, 2022 | Training Data 101
The quality of your annotations and training data depends on how well your annotation workforce executes the tasks. Guides are readable instructions that help improve the quality of annotations created by your labelers. Diffgram allows you to create detailed guides...
by Team Diffgram | Feb 22, 2022 | Training Data 101
You can better leverage Diffgram when your team perfectly knows how to label data for machine learning efforts. Diffgram’s data labeling tool allows you to effectively manage your data labeling tasks without having to leave the platform. No more isolated tools....
