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90 changes: 90 additions & 0 deletions docs/examples/20_basic/README.txt
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Expand Up @@ -2,3 +2,93 @@ Introductory Examples
=====================

Introductory examples to the usage of the OpenML python connector.
# Extended Examples

This directory contains advanced tutorial examples demonstrating extended functionality of the OpenML Python API. These examples build upon the basic tutorials and focus on experiment management, runtime analysis, benchmarking, and advanced workflow operations.

-------------------------------------------------------------

## Prerequisites

Before running these examples, ensure you have:

* Python 3.8 or higher
* The OpenML Python package installed:

pip install openml

Some examples may also require additional libraries such as:

* scikit-learn
* pandas
* matplotlib
* seaborn

--------------------------------------------------------------

## Running the Examples

Navigate to this directory and run any script using:

python <script_name>.py

For example:

python fetch_runtimes_tutorial.py

--------------------------------------------------------------

## Example Scripts Overview

configure_logging.py
Demonstrates how to configure logging for OpenML workflows.

create_upload_tutorial.py
Shows how to create and upload datasets, flows, and runs.

custom_flow_.py
Explains how to define and use custom OpenML flows.

datasets_tutorial.py
Covers advanced dataset retrieval and usage.

fetch_evaluations_tutorial.py
Demonstrates how to retrieve evaluation results from OpenML.

fetch_runtimes_tutorial.py
Shows how to analyze runtime performance of machine learning runs.

flow_id_tutorial.py
Explains how to retrieve and work with OpenML flow identifiers.

flows_and_runs_tutorial.py
Demonstrates managing OpenML flows and experiment runs.

plot_svm_hyperparameters_tutorial.py
Visualizes hyperparameter tuning results.

run_setup_tutorial.py
Shows how to configure and execute OpenML runs.

study_tutorial.py
Explains how to work with OpenML studies.

suites_tutorial.py
Demonstrates usage of benchmark suites.

tasks_tutorial.py
Covers working with OpenML tasks.

task_manual_iteration_tutorial.py
Demonstrates manual iteration over task splits.

-----------------------------------------------------------

##Notes:

These examples are intended for users who are already familiar with the basics of OpenML and want to explore more advanced capabilities.

License

All examples are released under the BSD 3-Clause License.