Random forests to save human lives
Flash flood prediction using machine learning has proven capable in the U.S. and Europe; we're now bringing it to East Africa.
Data science
Data science ideas and resources.
Insights on scaling and integrating databases
An interview with Greg Meddles, technical lead for healthcare.gov.
Using microservices to evolve beyond the data lake
The better prepared you are to utilize all the data in your data lake, the more likely you are to be successful.
A guide to improving data integrity
Validating your data requires asking the right questions and using the right data.
Inside the Washington Post’s popularity prediction experiment
A peek into the clickstream analysis and production pipeline for processing tens of millions of daily clicks, for thousands of articles.
Good fences (between data science and production) make good neighbors
What data scientists need to know about production—and what production should expect from their data scientists.
Use deep learning on data you already have
Putting deep learning into practice with new tools, frameworks, and future developments.
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.
4 trends in security data science for 2017
How bots, threat intelligence, adversarial machine learning, and deep learning are impacting the security landscape.
Scaling Scala
Evaluating the state and development of Scala from a data engineering perspective.
The telecommunication industry’s unique position for new revenue opportunities in big data, IoT, and VR
Telcos must regain value from over-the-top services and develop new sources of revenue by leveraging their data and infrastructure.
Planning for advanced analytics
The O’Reilly Podcast: John Thuma on how businesses can get more than “what happened” from their data.
Ecosystem data architecture
The O’Reilly Podcast: Bob Montemurro on planning data systems to match needs.
If prejudice lurks among us, can our analytics do any better?
Technical and policy considerations in combatting algorithmic bias.
Leveraging analytics 1.0 for the analytics 2.0 revolution
Rather than hiring data scientists from outside, consider training your proto data scientists.
Strategies to validate your security detections
Machine learning to generate attack data and improve security analytics.
Pagan Kennedy on the art and science of serendipity
It's important in this age of big data to return the original meaning of serendipity and talk about it as a skill.
Repeatable sampling of data sets in BigQuery for machine learning
An efficient, fast, and repeatable selection method that works on very large data sets.
Damon Feldman on multi-model databases
O'Reilly Podcast: Working with databases that go beyond traditional models.
Real-time data for the real world
Close the time gap between analysis and action to bring about the next wave of improvements in efficiency and reliability—and magic.
Data and Democracy
This report explores how political data science helps to drive everything from overall strategy and messaging to individual voter contacts and advertising.
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.
Using behavioral data to improve customer satisfaction
Why cross-channel analytics are crucial to empowering business teams with a behavioral view of your customer.
The Industrial Internet of Things: Why you need to get up to speed fast
Start planning now to reap the many benefits of connected manufacturing.