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 |