1. Update config.yaml
2. Update secrets.yaml [Optional]
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 dvc.yaml
10. app.py

 Clone the repository

 https://github.com/Annamalai-Subramani/Kidney_disease_classification

conda create -n cnncls python=3.8 -y
conda activate cnncls

pip install -r requirements.txt

python app.py

MLFLOW_TRACKING_URI=https://dagshub.com/Annamalai-Subramani/Kidney_disease_classification.mlflow
MLFLOW_TRACKING_USERNAME=Annamalai-Subramani
MLFLOW_TRACKING_PASSWORD=5834dc456909f93114f5f78ede42333d46fdb630 \

Run this to export as env variables:

set MLFLOW_TRACKING_URI=https://dagshub.com/Annamalai-Subramani/Kidney_disease_classification.mlflow

set MLFLOW_TRACKING_USERNAME=Annamalai-Subramani

set MLFLOW_TRACKING_PASSWORD=5834dc456909f93114f5f78ede42333d46fdb630

python script.py

1. dvc init
2. dvc repro
3. dvc dag

MLflow

1. Its Production Grade

2. Trace all of your expriements

3. Logging & taging your model

   DVC

4. Its very lite weight for POC only

5. lite weight expriements tracker

6. It can perform Orchestration (Creating Pipelines)