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2 | 2 | 
 
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3 | 3 | ### Environment Setup  | 
4 | 4 | 
 
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5 |  | -- `environment_setup/requirements.txt` : It consist of list of python packages which are needed by the train.py to run successfully on host agent (locally).  | 
 | 5 | +- `environment_setup/requirements.txt` : It consists of a list of python packages which are needed by the train.py to run successfully on host agent (locally).  | 
6 | 6 | 
 
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7 |  | -- `environment_setup/install_requirements.sh` : This script prepare the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt  | 
 | 7 | +- `environment_setup/install_requirements.sh` : This script prepares the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt  | 
8 | 8 | 
 
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9 | 9 | - `environment_setup/iac-*.yml, arm-templates` : Infrastructure as Code piplines to create and delete required resources along with corresponding arm-templates.  | 
10 | 10 | 
 
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11 |  | -- `environment_setup/Dockerfile` : Dockerfile of a building agent containing Python 3.6 and all required packages.  | 
 | 11 | +- `environment_setup/Dockerfile` : Dockerfile of a build agent containing Python 3.6 and all required packages.  | 
12 | 12 | 
 
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13 |  | -- `environment_setup/docker-image-pipeline.yml` : An AzDo pipeline building and pushing [microsoft/mlopspython](https://hub.docker.com/_/microsoft-mlops-python) image.   | 
 | 13 | +- `environment_setup/docker-image-pipeline.yml` : An AzDo pipeline for building and pushing [microsoft/mlopspython](https://hub.docker.com/_/microsoft-mlops-python) image.   | 
14 | 14 | 
 
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15 | 15 | ### Pipelines  | 
16 | 16 | 
 
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17 |  | -- `.pipelines/azdo-base-pipeline.yml` : a pipeline template used by ci-build-train pipeline and pr-build-train pipelines. It contains steps performig linting, data and unit testing.    | 
18 |  | -- `.pipelines/azdo-ci-build-train.yml` : a pipeline triggered when the code is merged into **master**. It profrorms linting, data integrity testing, unit testing, building and publishing an ML pipeline.  | 
19 |  | -- `.pipelines/azdo-pr-build-train.yml` : a pipeline triggered when a **pull request** to the **master** branch is created. It profrorms linting, data integrity testing and unit testing only.  | 
 | 17 | +- `.pipelines/azdo-base-pipeline.yml` : a pipeline template used by ci-build-train pipeline and pr-build-train pipelines. It contains steps performing linting, data and unit testing.    | 
 | 18 | +- `.pipelines/azdo-ci-build-train.yml` : a pipeline triggered when the code is merged into **master**. It performs linting, data integrity testing, unit testing, building and publishing an ML pipeline.  | 
 | 19 | +- `.pipelines/azdo-pr-build-train.yml` : a pipeline triggered when a **pull request** to the **master** branch is created. It performs linting, data integrity testing and unit testing only.  | 
20 | 20 | 
 
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21 | 21 | ### ML Services  | 
22 | 22 | 
 
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28 | 28 | 
 
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29 | 29 | - `code/training/train.py` : a training step of an ML training pipeline.  | 
30 | 30 | - `code/evaluate/evaluate_model.py` : an evaluating step of an ML training pipeline.  | 
31 |  | -- `code/evaluate/register_model.py` : registers a new trained model if evaluation shows the new model is more performent than the previous one.  | 
 | 31 | +- `code/evaluate/register_model.py` : registers a new trained model if evaluation shows the new model is more performant than the previous one.  | 
32 | 32 | 
 
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33 | 33 | ### Scoring  | 
34 | 34 | - code/scoring/score.py : a scoring script which is about to be packed into a Docker Image along with a model while being deployed to QA/Prod environment.  | 
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