.. _examples:
Examples
========
Below are links to a variety of example workflows help you get started with using
SeisBench to optimise your ML workflows.
.. _dataset_basics:
Dataset basics
--------------
.. raw:: html
An introduction to the SeisBench dataset API.
.. _model_basics:
Model basics
------------
.. raw:: html
Get orientated with SeisBench models, learning how to load them and deploy to seismic streams.
.. _generator_pipelines:
Generator pipelines
-------------------
.. raw:: html
Use the in-built generator functionality in SeisBench to enhance your ML processing workflows.
.. _applied_stream_picking:
Deploy ML pickers
-----------------
.. raw:: html
Rapidly deploy ML models integrated in SeisBench to seismic streams.
.. _using_deep_denoiser:
Using DeepDenoiser
------------------
.. raw:: html
Denoising seismic waveform streams with DeepDenoiser in SeisBench.
.. _depth_phases:
Picking depth phases and determining earthquake depth
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.. raw:: html
Determining earthquake hypocentral depth using depth phase in SeisBench.
.. _training_phasenet:
Training ML models on seismic data
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.. raw:: html
Get started with training deep learning routines (PhaseNet) on a benchmark seismic dataset in SeisBench.
.. _training_denoiser:
Training Denoiser models
------------------------
.. raw:: html
Learn how to train a Denoiser model on a SeisBench dataset and create a noise dataset from continuous seismic data.
.. _creating_a_dataset:
Creating a dataset
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.. raw:: html
Learn how to create a dataset in SeisBench, using build-in functions and the obspy FDSN client as data source.
Building an event catalog with GaMMA
------------------------------------
.. raw:: html
Learn how to create an event catalog from raw waveforms and the metadata using SeisBench and the GaMMA associator.
Building an event catalog with PyOcto
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.. raw:: html
Learn how to create an event catalog from raw waveforms and the metadata using SeisBench and the PyOcto associator.