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German Phrase Classification with LSTM and FastAPI: This repository hosts a machine learning project that demonstrates the classification of German text phrases into predefined categories using a Long Short-Term Memory (LSTM) model.

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German Phrase Classification with LSTM and FastAPI

This repository contains a machine learning project that classifies German text phrases into predefined categories using a Long Short-Term Memory (LSTM) model. The project leverages FastAPI for serving the model via a REST API and is Dockerized for ease of deployment.

Project Overview

The goal of this project is to demonstrate an end-to-end machine learning pipeline which includes:

  • Data preprocessing and exploration.
  • Training an LSTM model for text classification.
  • Developing a FastAPI application to serve the model.
  • Containerizing the setup using Docker for easy deployment.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • Python 3.8+
  • Docker

Built With

  • FastAPI - The web framework used
  • TensorFlow - ML framework for training LSTM model
  • Docker - Containerization platform

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

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German Phrase Classification with LSTM and FastAPI: This repository hosts a machine learning project that demonstrates the classification of German text phrases into predefined categories using a Long Short-Term Memory (LSTM) model.

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