You can find here a list of the official notebooks and scrips provided by Hyperplane.
Also, we would like to list here interesting content created by the community. If you wrote some notebook(s) leveraging Hyperplane and would like be listed here, please open a Pull Request so it can be included under the Community notebooks.
| Notebook | Description |
|---|---|
| Data processing with DASK | Speed up data preprocessing with distributed DASK cluster on Hyperplane |
| Data prepcessing with Ray | speed up data preprocessing with distributed Ray cluster on Hyperplane |
| Data preprocessing with Spark | speed up data preprocessing with distributed spark on Ray clusters on Hyperplane |
| Question answering Tensorflow Training with Ray | Tensorflow training with distributed hyperparameter tuning on Ray cluster |
| CIFAR Pytorch Training with Ray | pytorch training with distributed hyperparameter tuning and MLFlow on Ray cluster |
| Ray Tune with MLFlow | Simple Ray Tune example wth MLFlow Tracking |
| Ray Tune Bayesian Optimization | A collection of Ray Tune scheduler examples |
| Speed up inference on large data with DASK | Advance example on speed inference with DASK by preload large model to DASK workers |
| Triton model prepration | Convert Pytorch Keras sklearn and xgboost model checkpoints for Triton serving |
| Hyperplane Triton service App | Triton client in a flask APP to be served as a Hyperplane service |
| Simple pipeline job | A basic pipeline to automate a jupyter notebook with parameterization |
| GraphQL within jupyter | Submit pipeline jobs using graphql queries within jupyter a notebook |