Fix links to notebooks broken because the notebooks were moved (#17446)

docs/ecosystem/index.md

@@ -21,7 +21,7 @@ ONNX Runtime functions as part of an ecosystem of tools and platforms to deliver
 * [Azure Container Instance: Facial Expression Recognition](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-inference-facial-expression-recognition-deploy.ipynb){:target="_blank"}
 * [Azure Container Instance: MNIST](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-inference-mnist-deploy.ipynb){:target="_blank"}
 * [Azure Container Instance: Image classification (Resnet)](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/deployment/onnx/onnx-modelzoo-aml-deploy-resnet50.ipynb){:target="_blank"}
-* [Azure Kubernetes Services: FER+](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb){:target="_blank"}
+* [Azure Kubernetes Services: FER+](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb){:target="_blank"}
 * [Azure IoT Sedge (Intel UP2 device with OpenVINO)](https://github.com/Azure-Samples/onnxruntime-iot-edge/blob/master/AzureML-OpenVINO/README.md){:target="_blank"}
 * [Automated Machine Learning](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb){:target="_blank"}
 

docs/execution-providers/TensorRT-ExecutionProvider.md

@@ -540,5 +540,5 @@ This example shows how to run the Faster R-CNN model on TensorRT execution provi
     ./onnxruntime_perf_test -r 1 -e tensorrt -i "trt_fp16_enable|true" /path/to/onnx/your_inferred_model.onnx
     ```
 
-Please see [this Notebook](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb) for an example of running a model on GPU using ONNX Runtime through Azure Machine Learning Services.
+Please see [this Notebook](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnx-inference-byoc-gpu-cpu-aks.ipynb) for an example of running a model on GPU using ONNX Runtime through Azure Machine Learning Services.
 

docs/execution-providers/community-maintained/TVM-ExecutionProvider.md

@@ -233,7 +233,7 @@ It is also possible to use a precompiled model.
 
 The compiled model can be obtained using the [OctoML platform](https://onnx.octoml.ai)
 or compiled directly (see **Support precompiled model** section in
-[Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnxruntime-tvm-tutorial.ipynb)
+[Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnxruntime-tvm-tutorial.ipynb)
 for more information on model compilation).
 
 In order to use the precompiled model, only need to pass two options:
@@ -247,7 +247,7 @@ the files of the precompiled model are located.
 You can read more about these options in section [Configuration options](#configuration-options) above.
 
 ## Samples
-- [Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/inference/notebooks/onnxruntime-tvm-tutorial.ipynb)
+- [Sample notebook for ResNet50 inference with TVM EP](https://github.com/microsoft/onnxruntime/blob/main/docs/python/notebooks/onnxruntime-tvm-tutorial.ipynb)
 
 ## Known issues
 - At this moment, the TVM EP has only been verified on UNIX/Linux and Windows systems.