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Dockerfile for v.6.1
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Nabeel committed Nov 5, 2019
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -6,7 +6,7 @@ Version 6.0 with major new updates has been released. Get it [here](https://gith

Deep Learning capabilities have been added through integration with Keras and Tensorflow. This offers powerful capabilities for sequence predictions and complex timeseries forecasting.

This release also includes the ability to use [Additional Regressors](https://facebook.github.io/prophet/docs/seasonality,_holiday_effects,_and_regressors.html#additional-regressors) with Prophet, allowing you to model more complex timeseries.
This release also includes the ability to use [Additional Regressors](docs/Prophet.md#additional-regressors) with Prophet, allowing you to model more complex timeseries.

## Table of Contents

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14 changes: 14 additions & 0 deletions docker/Dockerfile v.6.1
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# Use the previous version of qlik-py-tools as a parent image
FROM nabeeloz/qlik-py-tools:6.0

# Set the working directory to /qlik-py-tools/core
WORKDIR /qlik-py-tools/core

# Copy all files from the core subdirectory into the container
COPY ./core/* /qlik-py-tools/core/

# Make ports 80 and 50055 available to the world outside this container
EXPOSE 80 50055

# Run __main__.py when the container launches
CMD ["python", "__main__.py"]
2 changes: 1 addition & 1 deletion docs/README.md
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Expand Up @@ -6,7 +6,7 @@ Version 6.0 with major new updates has been released. Get it [here](https://gith

Deep Learning capabilities have been added through integration with Keras and Tensorflow. This offers powerful capabilities for sequence predictions and complex timeseries forecasting.

This release also includes the ability to use [Additional Regressors](https://facebook.github.io/prophet/docs/seasonality,_holiday_effects,_and_regressors.html#additional-regressors) with Prophet, allowing you to model more complex timeseries.
This release also includes the ability to use [Additional Regressors](Prophet.md#additional-regressors) with Prophet, allowing you to model more complex timeseries.

## Table of Contents

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