mlproject-with-mlflow

Workflows

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
10. Update the dvc.yaml

How to run the project

STEPS:

Clone the repository

https://github.com/Junying123/mlproject-with-mlflow

...

STEP 1: Create a conda environment after cloning the repository

conda create -n mlproj python=3.10 -y

STEP 2: Activate the conda environment

conda activate mlproj

STEP 3: Install the required packages into requirements.txt

pip install -r requirements.txt

### Finally run the command below to start the application
python app.py

Now,

open up your local host and port

MLFLOW

Documentation

cmd

• mlflow ui

dagshub

Documentation

MLFLOW_TRACKING_URI=https://dagshub.com/Junying123/mlproject-with-mlflow.mlflow MLFLOW_TRACKING_USERNAME=Junying123 MLFLOW_TRACKING_PASSWORD=d1023ea3bfd72e0c74fc52361692843278f6df0a python script.py

Run this export as env variable in the terminal

export MLFLOW_TRACKING_URI=https://dagshub.com/Junying123/mlproject-with-mlflow.mlflow
export MLFLOW_TRACKING_USERNAME=Junying123
export MLFLOW_TRACKING_PASSWORD=d1023ea3bfd72e0c74fc52361692843278f6df0a