From 02e095cd0c48f70d2c8e12dd1338b21c821dfbd7 Mon Sep 17 00:00:00 2001 From: binhnguyennus Date: Fri, 2 Aug 2019 08:08:23 +0800 Subject: [PATCH] Personalised Recommender Systems at BBC --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 089fdd6..b96a3d4 100644 --- a/README.md +++ b/README.md @@ -115,7 +115,7 @@ An organized reading list for illustrating the patterns of scalable, reliable, a * [Operate Kubernetes Reliably at Stripe](https://stripe.com/blog/operating-kubernetes) * [Kubernetes Traffic Routing (2 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/09/28/k8s-routing2/) * [Agrarian-Scale Kubernetes (3 parts) at New York Times](https://open.nytimes.com/agrarian-scale-kubernetes-part-3-ee459887ed7e) - * [Nanoservices at BBC Online](https://medium.com/bbc-design-engineering/powering-bbc-online-with-nanoservices-727840ba015b) + * [Nanoservices at BBC](https://medium.com/bbc-design-engineering/powering-bbc-online-with-nanoservices-727840ba015b) * [PowerfulSeal: Testing Tool for Kubernetes Clusters at Bloomberg](https://www.techatbloomberg.com/blog/powerfulseal-testing-tool-kubernetes-clusters/) * [Conductor: Microservices Orchestrator at Netflix](https://medium.com/netflix-techblog/netflix-conductor-a-microservices-orchestrator-2e8d4771bf40) * [Making 10x Improvement in Release Times with Docker and Amazon ECS at Nextdoor](https://engblog.nextdoor.com/how-nextdoor-made-a-10x-improvement-in-release-times-with-docker-and-amazon-ecs-35aab52b726f) @@ -664,6 +664,7 @@ An organized reading list for illustrating the patterns of scalable, reliable, a * [Content-based Video Relevance Prediction at Hulu](https://medium.com/hulu-tech-blog/content-based-video-relevance-prediction-b2c448e14752) * [Improving Photo Selection With Deep Learning at TripAdvisor](http://engineering.tripadvisor.com/improving-tripadvisor-photo-selection-deep-learning/) * [Personalized Recommendations for Experiences Using Deep Learning at TripAdvisor](https://www.tripadvisor.com/engineering/personalized-recommendations-for-experiences-using-deep-learning/) + * [Personalised Recommender Systems at BBC](https://medium.com/bbc-design-engineering/developing-personalised-recommender-systems-at-the-bbc-e26c5e0c4216) * [Machine Learning (2 parts) at Condé Nast](https://technology.condenast.com/story/handbag-brand-and-color-detection) * [Natural Language Processing and Content Analysis (2 parts) at Condé Nast](https://technology.condenast.com/story/natural-language-processing-and-content-analysis-at-conde-nast-part-2-system-architecture) * [Machine Learning Applications In The E-commerce Domain (4 parts) at Rakuten](https://techblog.rakuten.co.jp/2017/07/12/machine-learning-applications-in-the-e-commerce-domain-4/)