This repository contains code for building pipelines with TensorFlow Extended (TFX) components. The pipelines are designed for various machine learning (ML) operations, such as data preprocessing, model training, evaluation, and deployment.

To access the code, please check out the master branch of this repository.

The repository includes scripts and notebooks for:

• Data preprocessing using TFX components
• Model training and evaluation
• Deployment workflows
• And more

1. Clone the Repository: Clone this repository to your local machine using:

   git clone https://github.com/brempong21/MLOPS-WITH-TFX.git
   

2. Navigate to the Repository Directory: Enter the repository directory:

   cd MLOPS-WITH-TFX
   

3. Checkout the Master Branch: Switch to the master branch to access the code:

   git checkout master
   

4. Explore the Code: Explore the scripts and notebooks available in the repository to understand different ML operations and workflows.

To visualize the training progress and model metrics, you can set up a TensorBoard server by running every cell in the .ipynb and enter 'http://localhost:6006' in your browser

Contributions to this repository are welcome. If you have suggestions for improvements or would like to add new features, feel free to open an issue or submit a pull request.

This project is licensed under the MIT License.

Special thanks to the TensorFlow Extended (TFX) development team for providing the tools and components for building scalable and production-ready machine learning pipelines.