There often are much more Machine Learning application ideas than available data sets. We eliminate that bottleneck. Define labeling functions, label some examples by hand and train weak classifiers to get a fast export of probabilistic labels.
Labeling tasks can be very time costly which delays the deployment of machine learning solutions. We aim to assist you in speeding up the data labeling process so you can build models in days, not weeks.
Labeling can become an extremely time-consuming task, therefore leading to high costs (direct or as opportunity costs). E.g. projects with more than 50,000 records easily cost more than 10,000€ in labeling.
a one-time job
We faced that requirements can change in a Machine Learning project. This also accounts for labeling. That is why we built our platform to treat labeling as an evolving procedure. You can extract and add data at any time in the process.
When talking about Supervised Learning, labeled data is pure gold. Keeping it in a simple text file or as a column in an Excel spreadsheet does not live up to its value. With onetask, your labels are properly organized and easy to access.
Common data privacy regulations forbid the transmission of sensitive data to labeling services. In these cases, labeling must be done in-house. With onetask, this is no problem at all. Use our on-premises solution to leverage your labeling.