Skip to content

Introducing BigML Subscriptions + Flexible Usage Options

by on June 26, 2013

It’s been almost a month since we launched our “Spread the Word” program which gives free subscriptions to users who invite three or more friends to use BigML—and we’ve been thrilled with the response and the hundreds of new users that are tapping into the power of machine learning through BigML. We are now giving anyone the option to sign up for a paid subscription to our service (with special introductory pricing) so that you can perform unlimited predictive modeling at different task sizes–this complements the ability to use BigML for free in Development mode, as well as our long-standing pay-as-you-go option.

So let’s recap your BigML usage options:

Free!

To get started with predictive modeling we encourage users to leverage our free Development mode where you can build models, ensembles and evaluations up to 5MB in size.  Development mode also features inline sources for those of you interested in manually inputting data to simulate specific situations.  Learn more about how to use Development mode option here.  Note that in Development mode you cannot upload models to the gallery.

bigml_development_mode

Subscriptions

Subscriptions are great for anyone who has larger files and/or who wants to build many models or ensembles from their data sources.

You can sign up for monthly, quarterly or annual subscriptions at three levels:  the Starter Plan gives you the ability to run tasks up to 64MB, with a maximum of two parallel tasks; the Boosted Plan gives you up to 1GB maximum task size and you can run up to four parallel tasks; the Pro plan gives you up to 4GB maximum task size and you can run up to 8 parallel tasks. The maximum task size is simply the size of your dataset (which can be a subset of your data source), and parallel tasks are exactly that – the number of tasks that you’re having BigML run at once, whether it be creation of datasets, models, ensembles or evaluations.

Introductory pricing for the subscriptions starts at $30 per month, with further discounts if you purchase quarterly or annual plans.  If you want a custom plan (say you have small files but feel the need for speed and want more parallel tasks), just contact us and we’ll work something out.  Also note that students, public researchers and other non-profit workers can receive a 50% discount.

bigml_subscription_plans

Pay-as-you-go

For those who will do occasional predictive modeling, our pre-paid option provides great flexibility. With pay-as-you-go you purchase credits based on anticipated size of your datasets, models and number of predictions. Credits are deducted based on your actual usage, and can also be applied for any overages on subscription plans (for example, if you have a specific task that exceeds the size of a subscription).

bigml_credits

Virtual Private Clouds

bigml_vpc

For companies with stringent data requirements or who wish to integrate BigML with their own authentication system, BigML offers Virtual Private Clouds, which are dedicated servers residing on AWS.  VPCs are also idea for companies seeking a white label or custom skinned version of BigML – either for internal usage and/or for reseller purposes.  Stay tuned for more details on VPCs and other enterprise-centric offerings from BigML, or contact us for more information. 

As always, it costs nothing to create data sources of any size – these sources will be hosted on our servers for you for up to one year, and longer if you continue to use them.

You can see more details on all of these options on our updated pricing page. And remember, you can still earn a free subscription by inviting friends to sign up for BigML!

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: