- 2D Image Post-Processing Techniques and Algorithms (DIY Drones) — understanding how automated image matching and processing tools work means you can also get a better understanding how to shoot your images and what to prevent to get good matches.
- Scientists Need to Learn to Share — despite science’s reputation for rigor, sloppiness is a substantial problem in some fields. You’re much more likely to check your work and follow best data-handling practices when you know someone is going to run your code and parse your data.
- METRICS — Meta-Research Innovation Center at Stanford. John Ioannidis has a posse: connecting researchers into weak science, running conferences, creating a “journal watch”, and engaging policy makers. (says The Economist)
- Grafana — elegant dashboard for graphite (the realtime data graphing engine).
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Data science: Where are we going? - DJ Patil, the U.S. government's first Chief Data Scientist, looks at the future of data science at Strata + Hadoop World 2015 in San Jose.
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