# Python package for machine-learning aided data labelling

In a lot of cases unlabelled data needs to be transformed to labelled data. The best solution is to use (multiple) human classifiers. However, going to all the data by hand (i.e. in text-mining or image-processing) is often a daunting task. Is there software that can combine human classifiers and machine-learning techniques in real time? I am especially interested in python packages.

To illustrate, classifying images from video streams is very repetitive. After 100 images (from different streams) a machine-learning algorithm could be used to predict the labels given by the human classifier. The machine classifier might be very confident about some (un)seen samples and very uncertain about others. The human classifier can then focus on the uncertain samples helping the machine classifier to learn better what is does not yet know.

• Look for sloth Apr 18 '17 at 19:28
• github.com/cvhciKIT/sloth
– D.W.
Apr 18 '17 at 22:24
• Am I correctly that with sloth the computer is helping the human in labelling the images and not the other way around. I am looking for tools where humans and machines predict the same objective and they aid each other. Apr 19 '17 at 7:06