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ml-food-recommendation

TensorFlow Docker Google Colab LICENSE Docker Version Docker Pulls

Food Recommendation System using TensorFlow Recommenders (TFRS) and deployed using TensorFlow Serving.

Notebook: MamMates Food Recommendation

Dataset: Food Recommendation Dataset (Dummy)

Features ๐Ÿ’ก

Using MamMates Food Recommendation, you can get food recommendation based on the given id_user.

Prerequisites ๐Ÿ“‹

Usage โœจ

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-recommendation
  • Run the image:
docker run -p 8504:8504 --name ml-rec putuwaw/mammates-food-recommendation
curl -s https://raw.githubusercontent.com/MamMates/ml-food-recommendation/main/example.json | curl -X POST -d @- http://localhost:8504/v1/models/food_rec:predict
  • You will get the following response:
{
  "predictions": [
    {
      "output_1": [
        1.59945917, 1.14119792, 0.741919041, 0.635785818, 0.532811046,
        0.467606097, 0.457192838, 0.0975963473, 0.017279733, -0.0865440145
      ],
      "output_2": ["13", "14", "12", "2", "18", "20", "11", "10", "7", "9"]
    }
  ]
}

Development ๐Ÿ’ป

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

  • Clone this repository:
git clone https://github.com/MamMates/ml-food-recommendation.git
  • Update the model by changing the saved model in the model folder.

  • Build the Docker image:

docker build -t mammates-food-recommendation .
  • Run the image:
docker run -p 8504:8504 --name ml-rec mammates-food-recommendation
curl -d @example.json -X POST http://localhost:8504/v1/models/food_rec:predict
  • To stop the container:
docker stop ml-rec

Note

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

License ๐Ÿ“

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

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ml-food-recommendation's Issues

[DOCS] Set Up Repository

Background

As a developer, I want to make an easy process both in requesting features/report bugs and making pull requests.

Solution

Set up repository by adding .gitignore, and pull requests with issues template.

Additional information

Please also add LICENSE and .gitattributes to ignore .pb file.

[FEAT] Serving Model for Food Recommendation

Background

As a user, I want to get the list of my food recommendation.

Solution

Create food recommendation model using TensorFlow Recommenders and serve using TensorFlow Serving.

Additional information

Please also create the Dockerfile to serve the model.

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