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feature: Add Jumpstart example notebooks #3068

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feat: add example notebooks to jumpstart documentation
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40 changes: 37 additions & 3 deletions doc/overview.rst
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Expand Up @@ -573,15 +573,49 @@ Here is an example:
# When you are done using your endpoint
model.sagemaker_session.delete_endpoint('my-endpoint')

********************************************
Use Prebuilt Models with SageMaker JumpStart
********************************************
*********************************************************
Use SageMaker JumpStart Algorithms with Pretrained Models
*********************************************************

JumpStart for the SageMaker Python SDK uses model ids and model versions to access the necessary
utilities. This table serves to provide the core material plus some extra information that can be useful
in selecting the correct model id and corresponding parameters.

.. toctree::
:maxdepth: 2

doc_utils/jumpstart

Example notebooks
=================

JumpStart supports 15 different machine learning problem types. Below is a list of all the supported
problem types with a link to a Jupyter notebook that provides example usage.

Vision
- `Image Classification <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_image_classification/Amazon_JumpStart_Image_Classification.ipynb>`__
- `Object Detection <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_object_detection/Amazon_JumpStart_Object_Detection.ipynb>`__
- `Semantic Segmentation <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_semantic_segmentation/Amazon_JumpStart_Semantic_Segmentation.ipynb>`__
- `Instance Segmentation <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_instance_segmentation/Amazon_JumpStart_Instance_Segmentation.ipynb>`__
- `Image Embedding <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_image_embedding/Amazon_JumpStart_Image_Embedding.ipynb>`__

Text
- `Text Classification <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_classification/Amazon_JumpStart_Text_Classification.ipynb>`__
- `Sentence Pair Classification <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_sentence_pair_classification/Amazon_JumpStart_Sentence_Pair_Classification.ipynb>`__
- `Question Answering <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_question_answering/Amazon_JumpStart_Question_Answering.ipynb>`__
- `Named Entity Recognition <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_named_entity_recognition/Amazon_JumpStart_Named_Entity_Recognition.ipynb>`__
- `Text Summarization <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_summarization/Amazon_JumpStart_Text_Summarization.ipynb>`__
- `Text Generation <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_generation/Amazon_JumpStart_Text_Generation.ipynb>`__
- `Machine Translation <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_machine_translation/Amazon_JumpStart_Machine_Translation.ipynb>`__
- `Text Embedding <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_text_embedding/Amazon_JumpStart_Text_Embedding.ipynb>`__

Tabular
- `Tabular Classification (LightGBM & Catboost) <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_tabular_classification/Amazon_JumpStart_Tabular_Classification_LightGBM_CatBoost.ipynb>`__
- `Tabular Classification (XGBoost & Linear Learner) <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_tabular_classification/Amazon_JumpStart_Tabular_Classification_XGBoost_LinearLearner.ipynb>`__
- `Tabular Regression (LightGBM & Catboost) <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_tabular_regression/Amazon_JumpStart_Tabular_Regression_LightGBM_CatBoost.ipynb>`__
- `Tabular Regression (XGBoost & Linear Learner) <https://github.com/aws/amazon-sagemaker-examples/blob/main/introduction_to_amazon_algorithms/jumpstart_tabular_regression/Amazon_JumpStart_Tabular_Regression_XGBoost_LinearLearner.ipynb>`__


`Amazon SageMaker JumpStart <https://aws.amazon.com/sagemaker/getting-started/>`__ is a
SageMaker feature that helps users bring machine learning (ML)
applications to market using prebuilt solutions for common use cases,
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