Data Science algorithms for Qlik implemented as a Python Server Side Extension (SSE).
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for updating on Windows
If you're on PyTools v.8.0, you can simply copy the files from the zip file above under the core folder and overwrite the files at qlik-py-tools\qlik-py-env\core
. Then just restart the SSE.
For older releases, you'll need to download the zip file above, extract it and run Qilk-Py-Init
as an administrator. Any model's trained previously will need to be re-trained.
This release adds the capability to use pre-trained scikit-learn, Keras and REST API based models with Qlik. Read more here.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for updating on Windows
You'll need to download the zip file above, extract it and run Qilk-Py-Init
as an administrator. Any model's trained previously will need to be re-trained.
This release adds the capability to use pre-trained scikit-learn, Keras and REST API based models with Qlik. Read more here.
With version 6, Deep Learning capabilities were added through integration with Keras and Tensorflow. This offers powerful capabilities for sequence predictions and complex timeseries forecasting.
PyTools now also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for updating on Windows
If you're on PyTools v.7.0 or above, you can simply copy the files from the zip file above under the core folder and overwrite the files at qlik-py-tools\qlik-py-env\core
. Then just restart the SSE.
If you're on a release older than 7.0, you'll need to download the zip file above, extract it and run Qilk-Py-Init
as an administrator. Any model's trained previously will need to be re-trained.
This release adds the capability to use pre-trained scikit-learn and Keras models with Qlik. Read more here.
With version 6, Deep Learning capabilities were added through integration with Keras and Tensorflow. This offers powerful capabilities for sequence predictions and complex timeseries forecasting.
PyTools now also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for updating on Windows
If you're on PyTools v.7.0 or above, you can simply copy the files from the zip file above under the core folder and overwrite the files at qlik-py-tools\qlik-py-env\core
. Then just restart the SSE.
If you're on a release older than 7.0, you'll need to download the zip file above, extract it and run Qilk-Py-Init
as an administrator. Any model's trained previously will need to be re-trained.
This release adds the capability to use pre-trained scikit-learn and Keras models with Qlik. Read more here.
With version 6, Deep Learning capabilities were added through integration with Keras and Tensorflow. This offers powerful capabilities for sequence predictions and complex timeseries forecasting.
PyTools now also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for updating on Windows
This release includes new Python packages so you can't simply replace the core
files. You'll need to download the zip file above, extract it and run Qilk-Py-Init
as an administrator. Any model's trained previously may need to be re-trained.
This release adds the capability to use pre-trained scikit-learn and Keras models with Qlik. Read more here.
With version 6, Deep Learning capabilities were added through integration with Keras and Tensorflow. This offers powerful capabilities for sequence predictions and complex timeseries forecasting.
PyTools now also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for a quick update on Windows
If you're on PyTools v.6.0 or above, you can simply copy the files from the zip file above under the core
folder and overwrite the files at qlik-py-tools\qlik-py-env\core
. Then just restart the SSE.
holidays
package release (Issue #89).Exciting new capabilities for Deep Learning with Keras and Tensorflow. You can now train and use neural networks for sequence predictions and complex timeseries forecasting.
This release also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for a quick update on Windows
If you're on PyTools v.6.0 or above, you can simply copy the files from the zip file above under the core
folder and overwrite the files at qlik-py-tools\qlik-py-env\core
. Then just restart the SSE.
return=residual
in the parameters.Exciting new capabilities for Deep Learning with Keras and Tensorflow. You can now train and use neural networks for sequence predictions and complex timeseries forecasting.
This release also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Tips for a quick update on Windows
If you're on PyTools v.6.0 or above, you can simply copy the files from the zip file above under the core
folder and overwrite the files at qlik-py-tools\qlik-py-env\core
. Then just restart the SSE.
Exciting new capabilities for Deep Learning with Keras and Tensorflow. You can now train and use neural networks for sequence predictions and complex timeseries forecasting.
This release also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Exciting new capabilities for Deep Learning with Keras and Tensorflow. You can now train and use neural networks for sequence predictions and complex timeseries forecasting.
This release also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.
This zip archive only contains the files needed to deploy the SSE. You can get sample Qlik Sense apps from the docs or download the full source code below.
Exciting new capabilities for Deep Learning with Keras and Tensorflow. You can now train and use neural networks for sequence predictions and complex timeseries forecasting.
This release also includes the ability to use Additional Regressors with Prophet, allowing you to model more complex timeseries.
For more information refer to the Usage section.
For more information refer to the Usage section.