Introducing Humanloop ProgrammaticJordan Burgess
Introducing Humanloop Programmatic
We’re delighted to offer early access to Humanloop Programmatic. A new kind of annotation tool that’s the fastest way to get annotated data for NLP.
Save time and cost by replacing manual labeling with rapid, programmatic labeling using Programmatic.
In working with hundreds of NLP teams over the last year, we've seen that getting annotated data is often the biggest bottleneck. Manual annotation is slow and expensive, and getting time from subject-matter experts can be difficult. As part of our mission is to solve this, we are making programmatic labeling accessible and practical.
With Programmatic, data scientists and machine learning engineers can label millions of datapoints in the time it would take to manually annotate hundreds.
It runs locally, keeping your data private. You can explore your data with powerful search. And you can rapidly iterate on labeling functions to take best advantage of subject-matter expertise.
You can export your labeled data to your machine learning pipeline or you can export to Humanloop to train a model and improve your dataset with active learning.
Here’s how Programmatic works
Here’s what users are saying about Programmatic:
I've been using the new Weak Labelling tool made by @HumanloopML for a Named Entity Recognition project. It is phenomenal.— Henry Maguire (@hejmaguire) March 7, 2022
It basically allows you to bootstrap massive NLP datasets to train machine learning models on, with just a few lines of code/regex.
Recently used @humanloopml's new programmatic labelling tool for named entity recognition, I went from no labels to 300k in a day.— Jonathan Bourne (@sse_data) March 4, 2022
Programmatic doesn't just make projects easier it makes projects that were impossible straight foreword and easy to understand. Pure 🔥🔥🔥
To understand more about how Weak Labeling can be so powerful read why I changed my mind about weak labeling for ML.
Programmatic is now in early access and you can sign up for immediate access for FREE using the following form.
About the author
- Jordan Burgess
- Cofounder and Chief Product Officer