Deep automation in machine learning
We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline.
Data science ideas and resources.
Ideas
Managing risk in machine learning
Considerations for a world where ML models are becoming mission critical.
Handling real-time data operations in the enterprise
Getting DataOps right is crucial to your late-stage big data projects.
The ethics of data flow
If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows.
It's time to establish big data standards
The deployment of big data tools is being held back by the lack of standards in a number of growth areas.
5 findings from O'Reilly's machine learning adoption survey companies should know
New survey results highlight the ways organizations are handling machine learning's move to the mainstream.
Learning
Video
A lesson in prescriptive modeling
Simulate new business models and practices with open source code.
Runnable code
Probabilistic programming from scratch
Working with uncertainty in real-world data.
Video
The Offline Challenge: Delivering Mobile Apps that Always Work
Wayne Carter and Ali LeClerc show you how to build a mobile app that has a consistent user experience, both online and offline.
Runnable code
Strategies to validate your security detections
Machine learning to generate attack data and improve security analytics.
Runnable code
Repeatable sampling of data sets in BigQuery for machine learning
An efficient, fast, and repeatable selection method that works on very large data sets.
Video
Solving the right problem
Max Shron and Sasha Laundy explore tactics for need-finding and problem scoping that make it possible to put investments in data to profitable use.