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docs(AutoML, AutoRAG): Tutorials updates. (#80)
* Feature: AutoML time series forecasting tutorial (electricity sample) (#62) * Replace main branch with rhoai-3.4 in autorag .md files * docs: Updated Workbech section and documentation links (#69) Assisted By Cursor Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * automl time-series tutorial draft Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Assisted-by: Cursor * Update time_series_forecasting_tutorial.md Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Assisted-by: Cursor * promo known_covariates_names example added Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Assisted-by: Cursor * replace the git urls from autox to main Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Assisted-by: Cursor # Conflicts: # examples/autorag/readme.md * clean up the dev preview status mentions Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Assisted-by: Cursor * adding time-series pipeline to readme Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Assisted-by: Cursor * Change branch reference from main -> rhoai-3.4. Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * Improved formatting, and notebook section Assisted by Cursor Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * docs: Updated Workbech section and documentation links Assisted By Cursor Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * chore: AutoML examples update how to get artifacts Assisted by Cursor Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * chore: Updated Model registry anbd deployment steps Signed-off-by: Dorota Laczak <dlaczak@redhat.com> --------- Signed-off-by: Dorota Laczak <dlaczak@redhat.com> Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Co-authored-by: Michal Steczko <msteczko@redhat.com> Co-authored-by: Dorota Laczak <dlaczak@redhat.com> * updated images * updated image Signed-off-by: ZabinskiMichal <mzabinsk@redhat.com> * updated images * updated pipeline (#72) * Custom column names in TS scenario tutorial update (#73) * updated tutorial * deleted unnecessary instrucion part * last small change * Update documentation with the latest UI changes (#75) Signed-off-by: MichalSteczko <msteczko@redhat.com> * chore: Removed pipeline.yaml file for AutoRAG (#79) Assisted by Cursor Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * docs(AutoML): Updated AutoML tutorials with UI path (#77) updatedTabular and TimeSeries tutorials to new UI flow * chore: Fixed for issues found by Markdownlinter Assisted by Claude Code Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * chore: Fixed issues found by CodeRabbit in PR review. Assisted by Claude Code Signed-off-by: Dorota Laczak <dlaczak@redhat.com> * chore: Updated KServe AutoGluon Server repo link Signed-off-by: Dorota Laczak <dlaczak@redhat.com> --------- Signed-off-by: Dorota Laczak <dlaczak@redhat.com> Signed-off-by: Lukasz Cmielowski <lcmielow@redhat.com> Signed-off-by: ZabinskiMichal <mzabinsk@redhat.com> Signed-off-by: MichalSteczko <msteczko@redhat.com> Co-authored-by: Lukasz Cmielowski <lcmielow@redhat.com> Co-authored-by: Michal Steczko <msteczko@redhat.com> Co-authored-by: ZabinskiMichal <mzabinsk@redhat.com> Co-authored-by: Michał Żabiński <85452231+ZabinskiMichal@users.noreply.github.com>
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# Time series sample data
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## Electricity demand (primary tutorial dataset)
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The file **`input_data/electricity_industry_a_forecasting.csv`** is derived from open data published in [IBM watsonx-ai-samples](https://github.com/IBM/watsonx-ai-samples/tree/master/cloud/data):
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- **Source:** [`cloud/data/electricity/electricity_usage.csv`](https://github.com/IBM/watsonx-ai-samples/blob/master/cloud/data/electricity/electricity_usage.csv) (columns `date`, `industry_a_usage`).
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- **Transformation:** A constant series id was added and columns were renamed so the CSV matches the [autogluon timeseries training pipeline](https://github.com/red-hat-data-services/pipelines-components/tree/main/pipelines/training/automl/autogluon_timeseries_training_pipeline) expectation: `item_id`, `timestamp`, `target`. All rows use `item_id` = `industry_a` (single series).
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Use this file with `id_column`=`item_id`, `timestamp_column`=`timestamp`, `target`=`target`, and no known covariates unless you enrich the data yourself.
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## Synthetic multi-series (optional)
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**`input_data/timeseries_sales.csv`** — small synthetic dataset aligned with the pipeline component [test data](https://github.com/red-hat-data-services/pipelines-components/blob/main/pipelines/training/automl/autogluon_timeseries_training_pipeline/tests/data/timeseries_sales.csv) on branch `main`; includes optional covariate `promo` for `known_covariates_names`.

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