madanuaugustin/winequalityprediction_with_mlflow

WineQualityPrediction_with_MLflow

Workflow

1. update config.yaml
2. update schema.yaml

3. update params.yaml

4. update the entity

5. update the configuration manager in src config
6. update the components
7. update the pipeline
8. update the main.py
9. update the app.py

How to run?

STEPS:

Clone the repository

https://github.com/entbappy/End-to-end-Machine-Learning-Project-with-MLflow

STEP 01- Create a conda environment after opening the repository

conda create -n mlproj python=3.8 -y

conda activate mlproj

STEP 02- install the requirements

pip install -r requirements.txt

# Finally run the following command
python app.py

Now,

open up you local host and port

Experiments & Model_registers

Link : https://dagshub.com/augustin7766/WineQualityPrediction_with_MLflow.mlflow/#/compare-experiments/s?experiments=%5B%2210%22,%2211%22,%2212%22,%2213%22,%2214%22,%2215%22,%2216%22,%2217%22,%228%22,%229%22%5D&searchFilter=&orderByKey=attributes.start_time&orderByAsc=false&startTime=ALL&lifecycleFilter=Active&datasetsFilter=W10%3D&modelVersionFilter=All%20Runs&selectedColumns=attributes.%60Source%60,attributes.%60Models%60,attributes.%60Dataset%60&compareRunsMode=CHART&compareRunCharts=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%3D

MLflow

Documentation

cmd

• mlflow ui

dagshub

dagshub

MLFLOW_TRACKING_URI=https://dagshub.com/augustin7766/WineQualityPrediction_with_MLflow.mlflow
MLFLOW_TRACKING_USERNAME=augustin7766
MLFLOW_TRACKING_PASSWORD=8a01ee4bec043666cf3ced22edc7d308526b4b42
python script.py

Run this to export as env variables:

# The below are the tracking URL's
# For windows OS use 'set' instead of 'export'
# performing the below commands in the terminal doesn't work instead we use package as shown in '05_model_evaluation.ipynb'

export MLFLOW_TRACKING_URI=https://dagshub.com/augustin7766/WineQualityPrediction_with_MLflow.mlflow

export MLFLOW_TRACKING_USERNAME=augustin7766

export MLFLOW_TRACKING_PASSWORD=8a01ee4bec043666cf3ced22edc7d308526b4b42