End-to-end-Machine-Learning-Project

Workflow

1. update config.yaml
2. update schema.yaml
3. update prams.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 dvc.yaml

How to run?

STEPS:

Clone the repository

https://github.com/podderSoykot/End-to-end-Machine-Learning-Project-main

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/podderSoykot/End-to-end-Machine-Learning-Project-main.mlflow MLFLOW_TRACKING_USERNAME=podderSoykot MLFLOW_TRACKING_PASSWORD=32a62a6b9e7119b292593d2b339676175b4441ae python script.py

Run this to export as env variables:

export MLFLOW_TRACKING_URI=https://dagshub.com/podderSoykot/End-to-end-Machine-Learning-Project-main.mlflow 

export MLFLOW_TRACKING_USERNAME=podderSoykot

export MLFLOW_TRACKING_PASSWORD=32a62a6b9e7119b292593d2b339676175b4441ae