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A web app which contains an end-to-end project of wine quality prediction

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pritesh2000/Wine_Quality_Prediction

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Wine_Quality_Prediction

Docker image of this project:

docker pull priteshtadvi/wine-quality-image:latest

Deployed on huggingface:

https://huggingface.co/spaces/pritesh29/Wine-Quality-Prediction

Workflows

  1. Update config.yaml
  2. Update schema.yaml
  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 app.py

How to run ?

Steps:

Clone the repository

git clone https://github.com/pritesh2000/Wine_Quality_Prediction

Step 1: Create a virtual environment after opening the repository

cd Wine_Quality_Prediction
virtualenv env

Based on CLI run

# for bash
source env/scripts/activate

or

# for command prompt
env\scripts\activate

Step 2: install the requirements

pip install -r requirements.txt
python app.py
Open up your localhost:8080 (make sure the port has not been used before).
Now app can run using trained data and predict the result

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A web app which contains an end-to-end project of wine quality prediction

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