ML_Intern/README.md

Concrete Compressive Strength

This project helps to predict the compressive strength of concrete after a given time at any time which in general takes 28 days time by the industry. The proposed Machine Learning Project is a time saver.

Acknowledgements

• Final Deployment
• GitHUB Repository
• DagsHUB Repository

Appendix

The Concrete compressive strength model is a Machine Learning project which predicts Concrete compressive strength on the basis of raw materials and age of the concrete.

Authors

• Amir Khan
• Fazlullah Bokhari

Badges

Add badges from somewhere like: shields.io

Environment Variables

To run this project, you will need to add the following environment variables to your .env file

API_KEY

ANOTHER_API_KEY

Configuration Setup

Command to the whole setup from scratch

For Virtual Environment and Requirements installation

  bash init_setup.sh

Activate the Environment

  conda activate ./env

Data Ingestion Step

  python src/Concrete_CS/pipeline/stage_01_data_ingestion.py

Data Validation Step

  python src/Concrete_CS/pipeline/stage_02_data_validation.py

Data Transformation Step

  python src/Concrete_CS/pipeline/stage_03_data_transformation.py

Model Trainer Step

  python src/Concrete_CS/pipeline/stage_04_model_trainer.py

DVC

Used to know the Model Flow

To initialize DVC

  dvc init

To run the Pipeline

  dvc repro