ml-food-price

Food Price Prediction using Artificial Neural Network (ANN) and deployed using TensorFlow Serving.

Notebook: MamMates Food Price

Dataset: Food Price Dataset

Features 💡

Using MamMates Food Price, you can predict the price of the food based on its name, rating, and location.

Prerequisites 📋

• TensorFlow 2.14.0 or higher
• Docker 24.0.7 or higher
• scikit-learn 1.3.2 or higher

Usage ✨

If you already have Docker installed, you only need to run the following command:

• Pull the image from Docker Hub:

docker pull putuwaw/mammates-food-price

• Run the image:

docker run -p 8503:8503 --name ml-price putuwaw/mammates-food-price

• You can check that the model is already running by opening the browser and go to http://localhost:8503/v1/models/food_price

• To do prediction, you can use the following command:

curl -s https://raw.githubusercontent.com/MamMates/ml-food-price/main/example.json | curl -X POST -d @- http://localhost:8503/v1/models/food_price:predict

• You will get the following response:

{
  "predictions": [[13661.9189]]
}

Development 💻

If you want to develop this model, you can follow the steps below:

• Clone this repository:

git clone https://github.com/MamMates/ml-food-price.git

• Update the model by changing the saved model in the model folder.

• Build the Docker image:

docker build -t mammates-food-price .

• Run the image:

docker run -p 8503:8503 --name ml-price mammates-food-price

• You can check that the model is already running by opening browser and go to http://localhost:8503/v1/models/food_price

• To do prediction, you can use the following command:

curl -d @example.json -X POST http://localhost:8503/v1/models/food_price:predict

• To stop the container:

docker stop ml-price

Note

If you want to learn more about TensorFlow Serving, you can read the REST API documentation here.

License 📝

This project is licensed under the MIT License. See the LICENSE file for details.