This is my end to end project

Diamond Price Prediction

git init

git add abc.txt
git add .

git commit -m "this is my first commit"

git pull

bash your_file_name.sh

python setup.py install

another way you can mention -e . in your requirement file and you can run

pip install -r requirements.txt

MLflow

Documentation

local cmd

• mlflow ui

dagshub

dagshub

MLFLOW_TRACKING_URI=https://dagshub.com/Shashankb1910/Diamond_Price_Prediction-end-to-end-proj.mlflow
MLFLOW_TRACKING_USERNAME=Shashankb1910
MLFLOW_TRACKING_PASSWORD=40aea5dfc244c1f1f09fc9d0e267b9bf72ddcb38
python script.py

Run this to export as env variables: #For cmd use "set" instead of export

export MLFLOW_TRACKING_URI=https://dagshub.com/Shashankb1910/Diamond_Price_Prediction-end-to-end-proj.mlflow 

export MLFLOW_TRACKING_USERNAME=Shashankb1910

export MLFLOW_TRACKING_PASSWORD=40aea5dfc244c1f1f09fc9d0e267b9bf72ddcb38

DVC cmd

• dvc init
• dvc repro
• dvc dag

How to run this project ?

• Run training pipeline

For predicting diamond price on local

• Run app.py and then go to current log and open link

• For mlflow run - mlflow ui

• For dagshub - Open dagshub uri