| 1 |
Accelerating machine learning with the feature store service |
| 2 |
Careers at condé nast |
| 3 |
Natural language processing and content analysis at condé nast, part 2: system architecture |
| 4 |
Natural language processing and content analysis at condé nast, part 1: an overview |
| 5 |
10 for 10: a scenic tour of node.js 10 lts |
| 6 |
As you sow, so shall you reap: corporate sponsors***p of open source |
| 7 |
Content categorization at condé nast: from flat fields to structured relations***ps |
| 8 |
End-to-end testing the condé nast paywalls |
| 9 |
Picking trending topics and celebrities using machine learning |
| 10 |
Celebrating women in tech: stories from condé nast |
| 11 |
Going extraordinary places with development |
| 12 |
The vogue augmented reality experience: how we did ıt |
| 13 |
Testing our brand sites at condé nast: from manual to automated |
| 14 |
Evolving google amp at condé nast |
| 15 |
Machine learning at condé nast, part 2: handbag brand and color detection |
| 16 |
Machine learning at condé nast, part 1: a neural network primer |
| 17 |
Departures or how condé nast stopped worrying and learned to love containers |
| 18 |
Progressive web apps? no, we are building alien web apps |
| 19 |
Ok google, talk to vogue |
| 20 |
The why and how of google amp at condé nast |
| 21 |
Condé nast goes to oscon |
| 22 |
How we did ıt: building "game of unknowns" on vanityfair.com |
| 23 |
Securing w magazine: our migration to https |
| 24 |
Bot-building with launch-vehicle-fbm |
| 25 |
What’s next at condé nast? |
| 26 |
Building our robot future |
| 27 |
Graph(ql)ing vogue |
| 28 |
Building a foundation for data at condé nast |
| 29 |
How we stopped talking about a blog and finally started one |