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### Articles
* [Machine Learning System Design](https://medium.com/@ricomeinl/machine-learning-system-design-f2f4018f2f8).
* [How to Code Neat Machine Learning Pipelines](https://www.neuraxio.com/en/blog/neuraxle/2019/10/26/neat-machine-learning-pipelines.html).
### Courses
* [Coursera's Big Data Pipeline course](https://www.coursera.org/lecture/big-data-integration-processing/big-data-processing-pipelines-c4Wyd).
### Tools
* [Airflow resources](https://github.com/bt3gl/Curated_ETL-and-ML-Pipelines/blob/master/airflow.md).
* [Data science resources](https://github.com/davidyakobovitch/data_science_resources).
* [AWS Data pipeline samples](https://github.com/aws-samples/data-pipeline-samples/tree/master/samples).
* [Lorte data pipelining](https://github.com/instacart/lore).
### Videos
* [Industrial Machine Learning Talk](https://www.youtube.com/watch?v=3JYDT8lap5U).
### Enterprise Solutions
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* [Remind data pipeline](https://medium.com/@RemindEng/beyond-a-redshift-centric-data-model-1e5c2b542442).
* [Wish data pipeline](https://medium.com/wish-engineering/scaling-analytics-at-wish-619eacb97d16).
* [Databrick data pipeline](https://databricks.com/blog/2017/03/31/delivering-personalized-shopping-experience-apache-spark-databricks.html).