Interactive Dashboards in DataRobot—Big Data and ML
This post was originally part of the DataRobot Community. Visit now to browse discussions and ask questions about DataRobot, AI Cloud, data science, and more.
There is no point in collecting large chunks of big data if you cannot interact with it and harness the information contained. Many people new to Data Science & Big Data struggle with this, which is not surprising. Most tutorials focus either on building models or visualizing existing big data; they don’t explain how to do both.
In this learning session, we focus on how to generate insights from big data and the factors you need to consider when building your scoring pipeline for interactive dashboards.
- Felix Huthmacher (DataRobot, AI Engineer)
- Reagan Yarema (DataRobot, AI Success)
After watching the learning session, you should check out these resources for more information.
- DataRobot Public Documentation: Add deployments
- DataRobot.com webinars:
- Artificial Intelligence wiki: Scoring Data
We will contact you shortly
We’re almost there! These are the next steps:
- Look out for an email from DataRobot with a subject line: Your Subscription Confirmation.
- Click the confirmation link to approve your consent.
- Done! You have now opted to receive communications about DataRobot’s products and services.
Didn’t receive the email? Please make sure to check your spam or junk folders.
Accelerate Your AI Journey with the DataRobot Partner EcosystemMarch 28, 2023· 3 min read
How MLOps Enables Machine Learning Production at ScaleMarch 23, 2023· 4 min read
A New Era of Value-Driven AIMarch 16, 2023· 2 min read
AI projects have many more unknowns than traditional technology projects. You have to know the right use case to start with and know the value you can expect even before you start. You need to understand what data sources to go after and how to get the data ready. You have to pick the right model to meet expected performance goals. Train it, test it, tune it. The list goes on. While you are trying to figure all this out, organizational leaders expect results from their investments in AI faster than ever before.
As we see from countless examples, the demand for AI is at a fever pitch across every industry. Becoming AI-driven is no longer really optional. As AI continues to advance at such an aggressive pace, solutions built on machine learning are quickly becoming the new norm. To meet the demands of the modern world, we have to experiment fast, collaborate…
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…