https://github.com/data-pioneer/cement-strength-predictor
https://github.com/data-pioneer/cement-strength-predictor
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/data-pioneer/cement-strength-predictor
- Owner: data-pioneer
- Created: 2024-01-05T07:35:33.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-05T08:48:49.000Z (over 1 year ago)
- Last Synced: 2025-01-18T02:14:09.128Z (3 months ago)
- Language: Jupyter Notebook
- Size: 3.7 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Cement Compression Strength Prediction using hypertunning Random Forest Regression
## This repository contains the code and models for predicting the compression strength of cement using Random Forest Regression. The predictive model has been fine-tuned using Grid Cross-Validation Hyperparameter Tuning to achieve optimal performance.The project is deployed on Heroku, allowing for seamless access to the prediction model.
## I have used the following libraries for project implementation
- RandomForestRegression + GridCv: Model implementation
- Flask: Frontend implementation
- Heroku: Deployment
## Installation
1. Clone this repository to your local machine using:
git clone (https://github.com/data-pioneer/Cement-Strength-Predictor.git)
2. Install the required dependencies using pip:
pip install -r requirements.txt
## Usage
1. Run the main file by executing:
python app.py
2. The Url of app will be written on terminal, copy that url in browser.
- Now you can calculate the compression strength of cement.