# Machine Learning Engineering Case studies

Here is a compiled list of technical journey of different companies in applying and scaling up their machine learning systems.

[Google: Best Practices for Machine Learning](https://developers.google.com/machine-learning/guides/rules-of-ml)

[ByteDance: How Tik-Tok Wins The Social Media Recommendation System War (transcription)](https://leehanchung.github.io/2020-02-18-Tik-Tok-Algorithm/)

[NerdWallet: How NerdWallet Dialed Machine Leraning Up to 11](https://www.nerdwallet.com/blog/engineering/how-nerdwallet-dialed-machine-learning-up-to-11/)

[AI Dungeon: How we scaled AI Dungeon 2 to support over 1,000,000 users](https://medium.com/@aidungeon/how-we-scaled-ai-dungeon-2-to-support-over-1-000-000-users-d207d5623de9)

[Spotify: The Winding Road to Better Machine Learning Infrastructure Through Tensorflow Extended and Kubeflow](https://labs.spotify.com/2019/12/13/the-winding-road-to-better-machine-learning-infrastructure-through-tensorflow-extended-and-kubeflow/)

[How Trigo built a scalable AI development & deployment pipeline for Frictionless Retail](https://medium.com/pytorch/how-trigo-built-a-scalable-ai-development-deployment-pipeline-for-frictionless-retail-b583d25d0dd)
