Skip to content

Latest commit

 

History

History
66 lines (42 loc) · 1.24 KB

File metadata and controls

66 lines (42 loc) · 1.24 KB

End_to_End_ML_Project_with_mlflow_and_Deployment

How to run?

STEPS:

Clone the repository

https://github.com/rrizwan98/End_to_End_ML_Project_with_mlflow_and_Deployment.git

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

MLflow

Documentation

cmd
  • mlflow ui

dagshub

dagshub

MLFLOW_TRACKING_URI=https://dagshub.com/rrizwan98/End_to_End_ML_Project_with_mlflow_and_Deployment.mlflow
MLFLOW_TRACKING_USERNAME=rrizwan98
MLFLOW_TRACKING_PASSWORD=d685b0bd147ef96de518be68b7d128d4d70ca84f
python script.py

Run this to export as env variables:

export MLFLOW_TRACKING_URI=https://dagshub.com/rrizwan98/End_to_End_ML_Project_with_mlflow_and_Deployment.mlflow

export MLFLOW_TRACKING_USERNAME=rrizwan98 

export MLFLOW_TRACKING_PASSWORD=d685b0bd147ef96de518be68b7d128d4d70ca84f