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[FSTORE-1186] Adding tutorial for Polars #246

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Merged
merged 2 commits into from
Mar 14, 2024
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[FSTORE-1186] Adding tutorial for Polars #246

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20fce55
adding polars quickstart tutorial
manu-sj Mar 12, 2024
97f3913
adding introduction in polars tutorial and adding it to readme
manu-sj Mar 14, 2024
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1 change: 1 addition & 0 deletions README.md
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Expand Up @@ -63,6 +63,7 @@ In order to understand the tutorials you need to be familiar with general concep
- [WandB](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/integrations/wandb): Build a machine learning model with Weights & Biases.
- [Great Expectations](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/integrations/great_expectations): Introduction to Great Expectations concepts and classes which are relevant for integration with the Hopsworks MLOps platform.
- [Neo4j](integrations/neo4j): Perform Anti-money laundering (AML) predictions using Neo4j Graph representation of transactions.
- [Polars](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/advanced_tutorials/polars/quickstart.ipynb) : Introductory tutorial on using Polars.
- [Monitoring](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/integrations/monitoring): How to implement feature monitoring in your production pipeline.
- [Bytewax](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/integrations/bytewax): Real time feature computation using Bytewax.
- [Apache Beam](https://github.com/logicalclocks/hopsworks-tutorials/tree/master/integrations/java/beam): Real time feature computation using Apache Beam, Google Cloud Dataflow and Hopsworks Feature Store.
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