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-279
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21 files changed

+295
-279
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Diff for: ‎.gitignore

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@@ -13,6 +13,6 @@ docker-compose.override.yml
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logs/
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mage-ai.db
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mage_data/
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mlruns
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secrets/
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titanic_clean.csv
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mlruns

Diff for: ‎Dockerfile

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@@ -1,7 +1,7 @@
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FROM mageai/mageai:alpha
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ARG PROJECT_NAME=mlops
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ARG MAGE_CODE_PATH=/home/mage_code
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ARG MAGE_CODE_PATH=/home/src
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ARG USER_CODE_PATH=${MAGE_CODE_PATH}/${PROJECT_NAME}
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WORKDIR ${MAGE_CODE_PATH}

Diff for: ‎OLD/custom/inference.py

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This file was deleted.

Diff for: ‎docker-compose.yml

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@@ -8,7 +8,9 @@ services:
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ports:
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- 6789:6789
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volumes:
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- .:/$MAGE_CODE_PATH
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- .:/$MAGE_CODE_PATH # /home/src by default
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# Store the data output on local machine to easily debug
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- ~/.mage_data:/$MAGE_CODE_PATH/mage_data # /home/src/mage_data by default
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restart: on-failure:5
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networks:
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- app-network

Diff for: ‎mlops/settings.yaml

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@@ -3,5 +3,5 @@ projects:
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unit_1_data_preparation: {}
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unit_2_training: {}
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unit_3_observability: {}
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unit_4_running: {}
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unit_4_triggering: {}
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unit_5_deploying: {}

Diff for: ‎mlops/unit_2_training/pipelines/xgboost_training/metadata.yaml

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@@ -1,87 +1,92 @@
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blocks:
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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global_data_product:
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uuid: training_set
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downstream_blocks: []
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: Training set
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retry_config: null
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status: executed
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timeout: null
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type: global_data_product
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upstream_blocks: []
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uuid: training_set
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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file_source:
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path: null
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downstream_blocks:
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- xgboost
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- dashboard_data_source
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: xgboost Hyperparameter tuning
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retry_config: null
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status: executed
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timeout: null
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type: transformer
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upstream_blocks:
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- training_set
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uuid: hyperparameter_tuning/xgboost
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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file_source:
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path: null
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downstream_blocks:
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- dashboard_data_source
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: XGBoost
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retry_config: null
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status: executed
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timeout: null
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type: data_exporter
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upstream_blocks:
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- hyperparameter_tuning/xgboost
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uuid: xgboost
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- all_upstream_blocks_executed: true
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color: pink
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configuration:
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file_source:
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path: null
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downstream_blocks: []
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: Dashboard data source
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retry_config: null
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status: executed
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timeout: null
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type: custom
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upstream_blocks:
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- hyperparameter_tuning/xgboost
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- xgboost
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uuid: dashboard_data_source
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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global_data_product:
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uuid: training_set
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downstream_blocks:
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- xgboost
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: Training set
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retry_config: null
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status: executed
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timeout: null
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type: global_data_product
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upstream_blocks: []
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uuid: training_set
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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file_path: unit_2_training/transformers/hyperparameter_tuning/xgboost.py
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file_source:
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path: unit_2_training/transformers/hyperparameter_tuning/xgboost.py
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downstream_blocks:
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- xgboost
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- dashboard_data_source
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: xgboost Hyperparameter tuning
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retry_config: null
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status: executed
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timeout: null
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type: transformer
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upstream_blocks:
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- training_set
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uuid: hyperparameter_tuning/xgboost
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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file_path: unit_2_training/data_exporters/xgboost.py
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file_source:
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path: unit_2_training/data_exporters/xgboost.py
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downstream_blocks:
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- dashboard_data_source
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: XGBoost
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retry_config: null
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status: executed
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timeout: null
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type: data_exporter
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upstream_blocks:
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- training_set
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- hyperparameter_tuning/xgboost
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uuid: xgboost
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- all_upstream_blocks_executed: true
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color: pink
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configuration:
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file_path: unit_2_training/custom/dashboard_data_source.py
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file_source:
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path: unit_2_training/custom/dashboard_data_source.py
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downstream_blocks: []
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executor_config: null
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executor_type: local_python
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has_callback: false
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language: python
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name: Dashboard data source
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retry_config: null
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status: executed
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timeout: null
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type: custom
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upstream_blocks:
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- xgboost
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- hyperparameter_tuning/xgboost
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uuid: dashboard_data_source
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cache_block_output_in_memory: false
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callbacks: []
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concurrency_config: {}
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conditionals: []
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created_at: '2024-05-07 18:27:34.902705+00:00'
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created_at: "2024-05-07 18:27:34.902705+00:00"
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data_integration: null
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description: 'XGBoost is a scalable and efficient implementation of gradient boosted
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decision trees, a powerful ensemble machine learning technique. '
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description: "XGBoost is a scalable and efficient implementation of gradient boosted
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decision trees, a powerful ensemble machine learning technique. "
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executor_config: {}
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executor_count: 1
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executor_type: null
@@ -101,5 +106,5 @@ variables:
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early_stopping_rounds: 1
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max_depth: 1
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max_evaluations: 1
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variables_dir: /home/src/mage_data/unit_2_training
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variables_dir: /home/src/mage_data/unit_4_triggering
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widgets: []

Diff for: ‎mlops/unit_3_observability/pipelines/xgboost_training/metadata.yaml

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@@ -4,7 +4,8 @@ blocks:
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configuration:
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global_data_product:
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uuid: training_set
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downstream_blocks: []
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downstream_blocks:
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- xgboost
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executor_config: null
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executor_type: local_python
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has_callback: false
@@ -19,8 +20,9 @@ blocks:
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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file_path: unit_2_training/transformers/hyperparameter_tuning/xgboost.py
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file_source:
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path: null
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path: unit_2_training/transformers/hyperparameter_tuning/xgboost.py
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downstream_blocks:
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- xgboost
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- dashboard_data_source
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- all_upstream_blocks_executed: true
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color: null
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configuration:
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file_path: unit_2_training/data_exporters/xgboost.py
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file_source:
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path: null
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path: unit_2_training/data_exporters/xgboost.py
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downstream_blocks:
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- dashboard_data_source
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executor_config: null
@@ -53,13 +56,15 @@ blocks:
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timeout: null
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type: data_exporter
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upstream_blocks:
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- training_set
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- hyperparameter_tuning/xgboost
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uuid: xgboost
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- all_upstream_blocks_executed: true
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color: pink
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configuration:
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file_path: unit_2_training/custom/dashboard_data_source.py
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file_source:
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path: null
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path: unit_2_training/custom/dashboard_data_source.py
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downstream_blocks: []
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executor_config: null
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executor_type: local_python
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timeout: null
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type: custom
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upstream_blocks:
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- hyperparameter_tuning/xgboost
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- xgboost
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- hyperparameter_tuning/xgboost
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uuid: dashboard_data_source
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cache_block_output_in_memory: false
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callbacks: []
@@ -101,4 +106,5 @@ variables:
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early_stopping_rounds: 1
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max_depth: 1
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max_evaluations: 1
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variables_dir: /home/src/mage_data/unit_4_triggering
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widgets: []

Diff for: ‎mlops/unit_4_triggering/custom/dashboard_data_source.py

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@custom
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def source(
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model: Booster,
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settings: Tuple[
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Dict[str, Union[bool, float, int, str]],
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csr_matrix,
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Series,
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],
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model: Booster,
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**kwargs,
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) -> Tuple[Booster, csr_matrix, csr_matrix]:
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_, X_train, y_train = settings

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