5 key drivers for getting more value from your data
Considerations based on experience with Fortune 500 clients.
Data science ideas and resources.
Ideas
Lessons learned turning machine learning models into real products and services
Why model development does not equal software development.
How will the GDPR impact machine learning?
Answers to the three most commonly asked questions about maintaining GDPR-compliant machine learning programs.
How to build analytic products in an age when data privacy has become critical
Privacy-preserving analytics is not only possible, but with GDPR about to come online, it will become necessary to incorporate privacy in your data products.
How to run a custom version of Spark on hosted Kubernetes
Learn how Spark 2.3.0+ integrates with K8s clusters on Google Cloud and Azure.
Data engineers vs. data scientists
The two positions are not interchangeable—and misperceptions of their roles can hurt teams and compromise productivity.
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.