change notebooks links (#17857)

docs/get_started.md

@@ -94,10 +94,10 @@ Model Compression and Quantization
 
 Use OpenVINO’s model compression tools to reduce your model’s latency and memory footprint while maintaining good accuracy.
 
-* Tutorial - `OpenVINO Post-Training Model Quantization <https://docs.openvino.ai/nightly/notebooks/111-yolov5-quantization-migration-with-output.html>`__
-* Tutorial - `Quantization-Aware Training in TensorFlow with OpenVINO NNCF <https://docs.openvino.ai/nightly/notebooks/305-tensorflow-quantization-aware-training-with-output.html>`__
-* Tutorial - `Quantization-Aware Training in PyTorch with NNCF <https://docs.openvino.ai/nightly/notebooks/302-pytorch-quantization-aware-training-with-output.html>`__
-* `Model Optimization Guide <https://docs.openvino.ai/nightly/notebooks/openvino_docs_model_optimization_guide.html>`__
+* Tutorial - `OpenVINO Post-Training Model Quantization <notebooks/111-yolov5-quantization-migration-with-output.html>`__
+* Tutorial - `Quantization-Aware Training in TensorFlow with OpenVINO NNCF <notebooks/305-tensorflow-quantization-aware-training-with-output.html>`__
+* Tutorial - `Quantization-Aware Training in PyTorch with NNCF <notebooks/302-pytorch-quantization-aware-training-with-output.html>`__
+* `Model Optimization Guide <notebooks/openvino_docs_model_optimization_guide.html>`__
 
 Automated Device Configuration
 ------------------------------

docs/install_guides/configurations-for-intel-gpu.md

@@ -83,13 +83,13 @@ What’s Next?
 You can try out the toolkit with:
 
 
-`Python Quick Start Example <https://docs.openvino.ai/nightly/notebooks/201-vision-monodepth-with-output.html>`_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+`Python Quick Start Example <notebooks/201-vision-monodepth-with-output.html>`_ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
 
 Visit the :ref:`Tutorials <notebook tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
    
-  * `OpenVINO Python API Tutorial <https://docs.openvino.ai/nightly/notebooks/002-openvino-api-with-output.html>`__
-  * `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/nightly/notebooks/001-hello-world-with-output.html>`__
-  * `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/nightly/notebooks/205-vision-background-removal-with-output.html>`__
+  * `OpenVINO Python API Tutorial <notebooks/002-openvino-api-with-output.html>`__
+  * `Basic image classification program with Hello Image Classification <notebooks/001-hello-world-with-output.html>`__
+  * `Convert a PyTorch model and use it for image background removal <notebooks/205-vision-background-removal-with-output.html>`__
 
 `C++ Quick Start Example <openvino_docs_get_started_get_started_demos.html>`__ for step-by-step instructions on building and running a basic image classification C++ application.
 

docs/install_guides/installing-openvino-from-archive-windows.md

@@ -179,9 +179,9 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
 
    Visit the :ref:`Tutorials <notebook tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
 
-   * `OpenVINO Python API Tutorial <https://docs.openvino.ai/2022.3/notebooks/002-openvino-api-with-output.html>`___
-   * `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2022.3/notebooks/001-hello-world-with-output.html>`___
-   * `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2022.3/notebooks/205-vision-background-removal-with-output.html>`___
+   * `OpenVINO Python API Tutorial <notebooks/002-openvino-api-with-output.html>`__ 
+   * `Basic image classification program with Hello Image Classification <notebooks/001-hello-world-with-output.html>`__
+   * `Convert a PyTorch model and use it for image background removal <notebooks/205-vision-background-removal-with-output.html>`__
 
 .. tab:: Get started with C++
 

docs/install_guides/installing-openvino-pip.md

@@ -106,16 +106,16 @@ Now that you've installed OpenVINO Runtime, you're ready to run your own machine
 .. image:: https://user-images.githubusercontent.com/15709723/127752390-f6aa371f-31b5-4846-84b9-18dd4f662406.gif
    :width: 400
 
-Try the `Python Quick Start Example <https://docs.openvino.ai/2022.3/notebooks/201-vision-monodepth-with-output.html>`__ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
+Try the `Python Quick Start Example <notebooks/201-vision-monodepth-with-output.html>`__ to estimate depth in a scene using an OpenVINO monodepth model in a Jupyter Notebook inside your web browser.
 
 Get started with Python
 +++++++++++++++++++++++
 
 Visit the :doc:`Tutorials <tutorials>` page for more Jupyter Notebooks to get you started with OpenVINO, such as:
 
-* `OpenVINO Python API Tutorial <https://docs.openvino.ai/2022.3/notebooks/002-openvino-api-with-output.html>`__
-* `Basic image classification program with Hello Image Classification <https://docs.openvino.ai/2022.3/notebooks/001-hello-world-with-output.html>`__
-* `Convert a PyTorch model and use it for image background removal <https://docs.openvino.ai/2022.3/notebooks/205-vision-background-removal-with-output.html>`__
+* `OpenVINO Python API Tutorial <notebooks/002-openvino-api-with-output.html>`__
+* `Basic image classification program with Hello Image Classification <notebooks/001-hello-world-with-output.html>`__
+* `Convert a PyTorch model and use it for image background removal <notebooks/205-vision-background-removal-with-output.html>`__
 
 Run OpenVINO on accelerated devices
 +++++++++++++++++++++++++++++++++++