Merge branch 'main' into dev

README.md

@@ -486,8 +486,9 @@ P.P.S, Looking for guides and interviews on applying ML? 👉[`applyingML`](http
 7. [LyftLearn: ML Model Training Infrastructure built on Kubernetes](https://eng.lyft.com/lyftlearn-ml-model-training-infrastructure-built-on-kubernetes-aef8218842bb) `Lyft`
 8. ["You Don't Need a Bigger Boat": A Full Data Pipeline Built with Open-Source Tools](https://github.com/jacopotagliabue/you-dont-need-a-bigger-boat) ([Paper](https://arxiv.org/abs/2107.07346)) `Coveo`
 9. [Core Modeling at Instagram](https://instagram-engineering.com/core-modeling-at-instagram-a51e0158aa48) `Instagram`
-10. [Evolving Reddit’s ML Model Deployment and Serving Architecture](https://www.reddit.com/r/RedditEng/comments/q14tsw/evolving_reddits_ml_model_deployment_and_serving/) `Reddit`
-
+10. [Open-Sourcing Metaflow - a Human-Centric Framework for Data Science](https://netflixtechblog.com/open-sourcing-metaflow-a-human-centric-framework-for-data-science-fa72e04a5d9) `Netflix`
+11. [MLOps at GreenSteam: Shipping Machine Learning](https://neptune.ai/blog/mlops-at-greensteam-shipping-machine-learning-case-study) `GreenSteam`
+12. [Evolving Reddit’s ML Model Deployment and Serving Architecture](https://www.reddit.com/r/RedditEng/comments/q14tsw/evolving_reddits_ml_model_deployment_and_serving/) `Reddit`
 
 ## Practices
 1. [Practical Recommendations for Gradient-Based Training of Deep Architectures](https://arxiv.org/abs/1206.5533) ([Paper](https://arxiv.org/pdf/1206.5533.pdf)) `Yoshua Bengio`
@@ -504,7 +505,8 @@ P.P.S, Looking for guides and interviews on applying ML? 👉[`applyingML`](http
 11. [The problem with AI developer tools for enterprises](https://towardsdatascience.com/the-problem-with-ai-developer-tools-for-enterprises-and-what-ikea-has-to-do-with-it-b26277841661) `Databricks`
 12. [Maintaining Machine Learning Model Accuracy Through Monitoring](https://doordash.engineering/2021/05/20/monitor-machine-learning-model-drift/) `DoorDash`
 13. [Building Scalable and Performant Marketing ML Systems at Wayfair](https://www.aboutwayfair.com/careers/tech-blog/building-scalable-and-performant-marketing-ml-systems-at-wayfair) `Wayfair`
-14. [5 Steps for Building Machine Learning Models for Business](https://shopify.engineering/building-business-machine-learning-models) `Shopify`
+14. [Our approach to building transparent and explainable AI systems](https://engineering.linkedin.com/blog/2021/transparent-and-explainable-AI-systems) `LinkedIn`
+15. [5 Steps for Building Machine Learning Models for Business](https://shopify.engineering/building-business-machine-learning-models) `Shopify`
 
 ## Team structure
 1. [Engineers Shouldn’t Write ETL: A Guide to Building a High Functioning Data Science Department](https://multithreaded.stitchfix.com/blog/2016/03/16/engineers-shouldnt-write-etl/) `Stitch Fix`