BigML News, Issue #13, January 2015
BigML - Machine learning made easy

 

Hi <<Full Name>>,


BigML is kicking off 2015 with many new great capabilities that are included in our Winter 2015 Release, which we'll be sharing with you in a webinar on February 11 at 9:00 Pacific / 17:00 GMT.

Some key highlights from the release include:


 
Sample Service

BigML’s new Sample Service provides fast access to datasets that are kept in an in-memory cache which enables a variety of sampling, filtering and correlation techniques. We have leveraged BigML's sample service to create a Dynamic Scatterplot visualization that we’ve released into BigML Labs, and which we’ll showcase on the webinar.

 

G-Means Clusters

This latest addition to BigML’s unsupervised learning algorithms is ideal for when you may not know how many clusters you wish to build from your dataset. 

 

BigML Projects

We’re happy to introduce Projects to help you organize your machine learning resources. On the webinar we’ll show you how to create a project from a new data source and how to manage your associated tasks and workflows. 

 

Google Integration

With the Winter Release, you’ll now be able to add sources to BigML through Google Cloud Storage and Google Drive, similar to our prior integrations with Dropbox and Azure Data Marketplace. You can also now log into BigML using your Google ID. 

 

BigML Labs

Our team is constantly working on innovative applications built on top of BigML's API. We’re now unveiling several of these in early access through our “BigML Labs”. Join us to see in action two of our latest applications codenamed BigML GAS and BigML X. 
 

And More: 

We’ve also made many UI tweaks, API bindings updates, BigMLer enhancements and general improvements that we’ll highlight in the webinar as we show off the Winter Release.

Once again, webinar space is limited, so please register today! 

REGISTER

Our mailing address is:
BigML, Inc
2851 NW 9th Street
Suite D, Conifer Plaza Building
Corvallis, Oregon 97330

Add us to your address book


Copyright © 2015 BigML, Inc, All rights reserved.