We left Capital One to work on this problem full time and have been working with great customers like the US Space Force. We just launched our Unsupervised Model Zoo, which runs and compares 12 clustering and anomaly detection algorithms. Also, we implemented cluster tracking over time to show things like conceptual drift or changing populations in your dataset.
This tool with one click lets data scientists clean data (automatically!), set up cloud and processing around their models, explore differences between clusters, and work faster.
What I'm proudest of: We rebuilt many of these algorithms from scratch, achieving up to 10x speedups in comparison with open-source implementations like Nvidia Rapids, you can read more about how we did this in our technical paper here: (https://www.all.vision/technical-whitepaper).
Welcome to our first milestone in our journey of building powerful and easy to use unsupervised learning tools.
We have a free trial for anyone who signs up from this post. To get started, make an account at (https://all.vision/) and upload any unlabeled dataset to find patterns inside your data set.
