Linking pages
- Why data scientists shouldn’t need to know Kubernetes https://huyenchip.com/2021/09/13/data-science-infrastructure.html 121 comments
- GitHub - josephmisiti/awesome-machine-learning: A curated list of awesome Machine Learning frameworks, libraries and software. https://github.com/josephmisiti/awesome-machine-learning 58 comments
- Introducing Flyte: A Cloud Native Machine Learning and Data Processing Platform | by Allyson Gale | Lyft Engineering https://eng.lyft.com/introducing-flyte-cloud-native-machine-learning-and-data-processing-platform-fb2bb3046a59 19 comments
- GitHub - great-expectations/great_expectations: Always know what to expect from your data. https://github.com/great-expectations/great_expectations 9 comments
- GitHub - visenger/awesome-mlops: A curated list of references for MLOps https://github.com/visenger/awesome-mlops 2 comments
- Orchestrating Data Pipelines at Lyft: comparing Flyte and Airflow | by Constantine Slisenka | Lyft Engineering https://eng.lyft.com/orchestrating-data-pipelines-at-lyft-comparing-flyte-and-airflow-72c40d143aad?gi=76067277283d 2 comments
- PyCon US 2022 Welcomes 8 Early-Stage Companies To Startup Row https://pycon.blogspot.com/2022/04/startup-row-2022-lineup-announcement.html 1 comment
- MLOps - 2021 Year in review - MLOps Community https://mlops.community/mlops-2021-year-in-review/ 1 comment
- How to build a DAG based Task Scheduling tool for Multiprocessor systems using python | by Ramses Alexander Coraspe Valdez | ITNEXT https://coraspe-ramses.medium.com/how-to-build-a-dag-based-task-scheduling-tool-for-multiprocessor-systems-using-python-d11a093a835b?sk=cd97481b16fea0e941c32362eaded7c5 1 comment
- Top AI Tools/Platforms To Perform Machine Learning ML Model Monitoring - MarkTechPost https://www.marktechpost.com/2022/10/30/top-ai-tools-platforms-to-perform-machine-learning-ml-model-monitoring/ 1 comment
- Top MLOps Platforms/Tools to Manage the Machine Learning Lifecycle in 2022 - MarkTechPost https://www.marktechpost.com/2022/08/20/top-mlops-platforms-tools-to-manage-the-machine-learning-lifecycle-in-2022/ 0 comments
- Flyte Joins LF AI & Data. A little over a year ago on January… | by Anand Swaminathan | Lyft Engineering https://eng.lyft.com/flyte-joins-lf-ai-data-48c9b4b60eec 0 comments
- GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning https://github.com/EthicalML/awesome-production-machine-learning 0 comments
- How to build a DAG based Task Scheduling tool for Multiprocessor systems using python | by Ramses Alexander Coraspe Valdez | ITNEXT https://itnext.io/how-to-build-a-dag-based-task-scheduling-tool-for-multiprocessor-systems-using-python-d11a093a835b 0 comments
- We're still in the steam-powered days of machine learning https://vicki.substack.com/p/were-still-in-the-steam-powered-days 0 comments
- LyftLearn: ML Model Training Infrastructure built on Kubernetes | by Vinay Kakade | Lyft Engineering https://eng.lyft.com/lyftlearn-ml-model-training-infrastructure-built-on-kubernetes-aef8218842bb 0 comments
- Do Wide and Deep Networks Learn the Same Things? https://mlops.substack.com/p/do-wide-and-deep-networks-learn-the 0 comments
- Data Orchestration — A Primer. Data scientists and data engineers are… | by Astasia Myers | Memory Leak | Medium https://medium.com/memory-leak/data-orchestration-a-primer-56f3ddbb1700 0 comments
- GitHub - kelvins/awesome-mlops: A curated list of awesome MLOps tools https://github.com/kelvins/awesome-mlops 0 comments
- Orchestrating Data Pipelines at Lyft: comparing Flyte and Airflow | by Constantine Slisenka | Lyft Engineering https://eng.lyft.com/orchestrating-data-pipelines-at-lyft-comparing-flyte-and-airflow-72c40d143aad?gi=dc59382113b9 0 comments