DataRobot has long believed that to democratize machine learning (ML) on the path to Augmented Intelligence, any user must have seamless access to learning — for example, how to prepare, create, explore, deploy, monitor, and consume ML models. Those already familiar with the DataRobot experience are also familiar with our in-app documentation that makes it easy to keep up with our fast-paced product growth. However, for those investigating the platform — or perhaps more generally, machine learning — publicly accessible knowledge assets provide a huge leg-up to gain understanding and mastery. Often it’s more than simply understanding how; it’s an idea or vision sparked by seeing possibilities. 

When working with users, we often hear people say, “Wow, I didn’t know you could do that.” 

With our new public docs site, we now offer those revelations in the quiet of your own discovery.

Introducing docs.datarobot.com

Docs.datarobot.com is a one-stop-PUBLIC-shop for learning about all of DataRobot’s product offerings. With the new site, DataRobot further democratizes data science by releasing its significant platform documentation, API references, and tutorial content to the public. Any user can access the documentation, as well as DataRobot University, the Community, and the DataRobot website.

Here’s a preview of what you will find in each section:

• Platform: Our complete workflow documentation, from importing data to consuming models
• API: Links to all of our API reference guides as well as a quickstart 
• Tutorials: Quick explanations of tasks associated with each stage in the modeling process
• Notebooks: How to use and manage DataRobot Zepl notebook-powered data science
• Glossary: Definitions of key terms that are particularly important to understanding DataRobot

Another awesome addition to the site is an intuitive, natural language, filtered search that returns the help you need — in the format you want — to answer your questions.

Documentation for Existing Users

Already a user? You’ll find all of the content on the public site — and more — available from within the app. For example, let’s say you’re staring at the Profit Curve visualization and are curious as to the impact of changing costs or benefits. Click the in-app help to see full documentation — it’s right there.

But you can also use docs.datarobot.com for quick answers, to help explain concepts to non-users (share links), and to easily access other DataRobot resources. Need to explain to your university administrators how you know exactly why there is a segment of the population that is not going to be leaving their hallowed halls with the appropriate paper in hand? Send them a link to the SHAP documentation. 

When I started at DataRobot (hired to create the first docs five years ago), the documentation consisted of six “pages” of brilliant, sleep-deprived-derived, multilingual brain dumps. I immediately tossed it all and started again. It has been a true labor of love with an extraordinary team —touching all oceans — of writers, reviewers, developers, product managers, and translation folks. Of all the things I’ve written and the technologies I’ve learned (both machine learning and content platforms), nothing has been as satisfying or well received as the results of this new website. If you’ve worked with developers and data scientists — or are one — you know it’s a demanding and exacting audience. DataRobot believes in democratization across all aspects of learning, whether machine or human, and so the first readers of this new site are our own. And they are hooked. Our documentation is the product of cross-functional, all-hands-on-deck collaboration, review, and corrective reiteration. In other words, you can trust it — our data scientists do.

What’s Next?

What lies down the road? Upgrades to the site will include the ability to log in with your DataRobot account, providing access to the full user documentation. Search will return results across the DataRobot portfolio of learning content. And, of course, an ever-growing wealth of feature documentation, tutorials, and API tools. 

About the author

Jen Davies

Director of Technical Content at DataRobot

Jen leads a team of all-star technical writers at DataRobot — a department with the singular focus of making all phases of machine learning accessible and understandable to all.  She wrote the first words of the DataRobot documentation (and 20+ years of technical words before that) and is enthusiastically planning and implementing additional creative learning assets to continue the mission.

Meet Jen Davies

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Andrew Greenhut

Product Director at DataRobot

Andrew leads product for DataRobot’s Product-Led Growth team. Before that, he was the first data scientist at LogMeIn and a data science instructor for General Assembly. Prior to data science, he spent 5 years as an engineer in the defense industry. Andrew holds a B.S. and M.S. in Mechanical Engineering from MIT.

Meet Andrew Greenhut