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doc/changes/changes_1.0.0.md

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# data-science-examples 1.0.0, released 2020-XX-XX
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# data-science-examples 1.0.0, released 2023-10-16
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First release of this collection of examples for Integrating the Exasol Database with datascience
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focused applications and packages.
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## Features / Enhancements
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* # 21: Added an example for connecting from AWS Sagemaker to an Exasol database
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* # 23: Added an example for training a Sagemaker model with data from Exasol
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* # 25: Added an example for using a Sagemaker model from within Exasol
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* # 34: Added an example for loading example data into the Exasol database
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* # 43: Updated to Python3.8 minimal flavor in script-languages tutorial
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* #6: Added Tensorflow GPU UDF preview
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* #8: Added SciKit-learn classification Example
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* #21: Added an example for connecting from AWS Sagemaker to an Exasol database
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* #23: Added an example for training a Sagemaker model with data from Exasol
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* #25: Added an example for using a Sagemaker model from within Exasol
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* #29: Add script-languages build and customization tutorial
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* #34: Added an example for loading example data into the Exasol database
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* #35: Added tutorial for Sagemaker-Extension
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* #43: Updated to Python3.8 minimal flavor in script-languages tutorial
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* #45: Added error_code_config
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* #39-#48: Added tutorial Series for Connection to AzureML
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## Bugs
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* # 53: Fixed error_code_config.yaml
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* #53: Fixed error_code_config.yaml
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* #38: Fix typo
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tutorials/README.md

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* [Machine Learning](machine-learning)
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* [Python](machine-learning/python):
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* [AzureML](machine-learning/python/AzureML/Introduction.ipynb)
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* [Scikit-learn](machine-learning/python/scikit-learn)
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* [Sagemaker](machine-learning/python/sagemaker) Using AWS sagemaker for machine learning with Exasol
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* [SageMaker Extension](machine-learning/sagemaker-extension)
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* [Script-Language Container](script-languages)
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* [Spatial Analysis](spatial-analysis)
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* [Visualizing Spatial Queries](spatial-analysis/visualizing_spatial_queries)

tutorials/machine-learning/README.md

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## Machine Learning Tutorials
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This section contains tutorials for doing Machine Learning within the Exasol database. We are going to provide examples for different languages and frameworks, tasks and use cases.
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**Currently, this repository is under development and we will add more and more frameworks and tutorials in the future.**
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### Languages:
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* [Python](python)

tutorials/machine-learning/python/README.md

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## Python Tutorials
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This section contains tutorials with the Python Programming Language. We are going to provide examples for different frameworks, tasks and use cases.
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**Currently, this repository is under development and we will add more and more frameworks and tutorials in the future.**
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### AzureML:
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[AzureML](https://azure.microsoft.com/de-de/products/machine-learning) is a Microsoft service for the Machine
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learning lifecycle in Azure.
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This tutorial will show you:
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* [A general introduction to the topic](AzureML/Introduction.ipynb), we recommend you start here
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* [How to connect AzureML to Exasol](AzureML/ConnectAzureMLtoExasol.ipynb)
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* [How to Train a model using data from Exasol](AzureML/TrainModelInAzureML.ipynb)
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* [How to Invoke the trained model from an Exasol UDF](AzureML/InvokeModelFromExasolDBwithUDF.ipynb)
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### Frameworks:
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tutorials/spatial-analysis/README.md

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## Spatial Analysis Tutorials
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This section contains tutorials for doing Spatial Analysis within the Exasol database. We are going to provide examples, tasks and use cases.
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**Currently, this repository is under development and we will add more and more frameworks and tutorials in the future.**
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### Languages:
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* [Visualizing Spatial Queries](visualizing_spatial_queries)

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