Tutorials
=========

All of our Jupyter Notebook tutorials are directly accessible via `Binder <https://mybinder.org/>`__.
At Aidge, we're all about providing state-of-the-art, proven and reusable tools.
This Binder integration means you get a ready-to-use environment right in your browser, making our code immediately reproducible for everyone, everywhere.


To get started with Aidge, follow the Aidge demonstration tutorial.
This tutorial covers the basic features of the Aidge framework, including importing an ONNX model, transforming a neural network graph, running inference, and exporting to C++.

.. nbgallery::
    101_first_step.nblink
    aidge_ir.nblink


🛠 Aidge functionalities
------------------------

.. nbgallery::
    database.nblink
    graph_matching.nblink
    scheduling.nblink
    learning.nblink
    ONNX.nblink
    backend_cuda.nblink

🔍 Analysis tutorials
----------------------

.. nbgallery::
    model_explorer.nblink
    static_analysis.nblink
    benchmark.nblink


⚙️ Optimization tutorials
-------------------------

.. nbgallery::
    ptq.nblink
    tiling.nblink

🚀 Export tutorials
--------------------

.. nbgallery::
    export_cpp.nblink
    export_cpp_quant.nblink
    export_cpp_add_impl.nblink
    export_trt.nblink
    export_stm32.nblink

🔬📊 DNN uncertainty estimation
--------------------------------


.. nbgallery::
    CIFAR-10_vs_GTSRB_DNN_uncertainty_estimation_using_Monte_Carlo_Dropout.nblink
    Dropout_op_statistical_validation.nblink
    Inference_with_a_real_CIFAR-10_input_image.nblink


👨‍💻 Developer tutorials
-----------------------------

.. nbgallery::
    add_new_operator.nblink


If you encounter any difficulties with the tutorials, please create an issue `here <https://gitlab.eclipse.org/groups/eclipse/aidge/-/issues>`_.

For more information on contributing to Aidge, please refer to the `wiki <https://gitlab.eclipse.org/groups/eclipse/aidge/-/wikis/Contributing>`_.