Video Tutorial: https://youtu.be/ruIbk7N_qEc

The Height vs Age Predictor Microservice is a Flask-based web application that predicts heights based on ages. It uses a machine learning model trained on provided age and height data to generate predictions and visualize the relationship between age and height.

• Python 3.10
• Flask
• NumPy
• Scikit-learn
• Plotly
• Joblib

1. Ensure Python 3.10 is installed on your system.
2. Install the necessary dependencies using pip install -r requirements.txt.
3. Run the Flask app by executing python app.py from the project root.
4. Access the app in your browser at (https://flaskappregression.azurewebsites.net/)

1. Enter comma-separated ages into the input field.
2. Submit the form to receive a visualization of the predicted heights based on the provided ages.

Actionable Insights:

• Utilize this microservice as a tool for predicting heights based on age input, which could be valuable in various domains such as health, pediatrics, or educational research.
• Consider extending the microservice to handle larger datasets or additional features beyond age and height for more comprehensive predictive capabilities.

Data-Driven Decision Making:

• Leverage the model's predictions to gain insights into potential growth patterns or trends related to age and height, enabling data-driven decision-making in relevant fields.
• Explore ways to enhance the model's accuracy and robustness by incorporating more diverse datasets or utilizing advanced machine learning techniques.

Scalability and Deployment:

• Evaluate the microservice's scalability under increased user load to ensure seamless performance in production environments.

References https://learn.microsoft.com/en-us/azure/developer/python/tutorial-containerize-deploy-python-web-app-azure-03?tabs=azure-portal

https://www.jamessturtevant.com/posts/Deploying-Python-Website-To-Azure-Web-with-Docker/

https://learn.microsoft.com/en-us/azure/developer/python/tutorial-containerize-simple-web-app?tabs=web-app-flask

https://learn.microsoft.com/en-us/azure/app-service/deploy-github-actions?tabs=applevel#generate-deployment-credentials