[docs] update information about the project

README.md

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 # ml-food-classification
-Food Classification using Machine Learning
+
+![TensorFlow](https://img.shields.io/badge/TensorFlow-%23FF6F00.svg?style=for-the-badge&logo=TensorFlow&logoColor=white)
+![Keras](https://img.shields.io/badge/Keras-%23D00000.svg?style=for-the-badge&logo=Keras&logoColor=white)
+![Docker](https://img.shields.io/badge/docker-%230db7ed.svg?style=for-the-badge&logo=docker&logoColor=white)
+[![Google Colab](https://img.shields.io/badge/open_in_colab-blue?style=for-the-badge&logo=googlecolab&color=blue&labelColor=525252)](https://colab.research.google.com/github/MamMates/ml-food-classification/blob/main/MamMates_Food_Classification.ipynb)
+![LICENSE](https://img.shields.io/github/license/MamMates/ml-food-classification?style=for-the-badge)
+![Docker Version](https://img.shields.io/docker/v/putuwaw/mammates-food-classification/latest?style=for-the-badge)
+![Docker Pulls](https://img.shields.io/docker/pulls/putuwaw/mammates-food-classification?style=for-the-badge)
+
+Food Classification using Convolutional Neural Network (CNN) and deployed using TensorFlow Serving.
+
+Notebook: [MamMates Food Classification](https://colab.research.google.com/github/MamMates/ml-food-classification/blob/main/MamMates_Food_Classification.ipynb)
+
+Dataset: [MamMates Dataset](https://drive.google.com/drive/folders/1pTTSWZB4BYkS_rHxJ8ksni2A_fBt1i6e?usp=drive_link)
+
+## Features 💡
+
+Using Mammates Food Classification, you can categorize food images into 10 classes.
+
+| Class | Label        |
+| ----- | ------------ |
+| 0     | bika_ambon   |
+| 1     | dadar_gulung |
+| 2     | donat        |
+| 3     | kue_cubit    |
+| 4     | kue_klepon   |
+| 5     | kue_lapis    |
+| 6     | kue_lumpur   |
+| 7     | kue_risoles  |
+| 8     | putu_ayu     |
+| 9     | roti         |
+
+## Prerequisites 📋
+
+- [TensorFlow](https://www.tensorflow.org/) 2.14.0 or higher
+- [Docker](https://www.docker.com/) 24.0.7 or higher
+
+## Usage ✨
+
+If you already have Docker installed, you only need to run the following command:
+
+- Pull the image from Docker Hub:
+
+```bash
+docker pull putuwaw/mammates-food-classification
+```
+
+- Run the image:
+
+```bash
+docker run -p 8501:8501 --name ml-clf putuwaw/mammates-food-classification
+```
+
+- You can check that the model is already running by opening the browser and go to `http://localhost:8501/v1/models/food_clf`
+
+- To do prediction, you can use the following command:
+
+```bash
+curl -d @example.json -X POST http://localhost:8501/v1/models/food_clf:predict
+```
+
+- You will get the following response:
+
+```json
+{
+  "predictions": [
+    [
+      6.28405522e-11, 7.40732e-6, 0.998946607, 1.49191326e-8, 0.000139753625,
+      2.86315444e-5, 0.000863699941, 6.22894277e-7, 1.15933371e-5, 1.64414064e-6
+    ]
+  ]
+}
+```
+
+## Development 💻
+
+If you want to develop this model, you can follow the steps below:
+
+- Clone this repository:
+
+```bash
+git clone https://github.com/MamMates/ml-food-classification.git
+```
+
+- Update the model by changing the saved model in the [model](model/) folder.
+
+- Build the Docker image:
+
+```bash
+docker build -t mammates-food-classification .
+```
+
+- Run the image:
+
+```bash
+docker run -p 8501:8501 --name ml-clf mammates-food-classification
+```
+
+- You can check that the model is already running by opening browser and go to `http://localhost:8501/v1/models/food_clf`
+
+- To stop the container:
+
+```bash
+docker stop ml-clf
+```
+
+> [!NOTE]  
+> If you want to learn more about TensorFlow Serving, you can read the REST API documentation [here](https://www.tensorflow.org/tfx/serving/api_rest).
+
+## Acknowledgements 🙏
+
+Our sincere gratitude goes to the creators and maintainers of these datasets. Their generosity in sharing these resources has been instrumental in driving the progress and success of this project.
+
+- [Deteksi Makanan Daerah Dataset](https://universe.roboflow.com/fusion-qvvyj)
+- [Indonesian Food Dataset](https://universe.roboflow.com/bangkit)
+- [Food 101 Dataset](https://www.kaggle.com/datasets/dansbecker/food-101)
+- [Food-5K Dataset](https://www.epfl.ch/labs/mmspg/downloads/food-image-datasets/)
+- [Food-11 Dataset](https://www.kaggle.com/datasets/trolukovich/food11-image-dataset)
+
+## License 📝
+
+This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.