Building Machine Learning Applications With Streamlit ✨

📚 Description

Welcome to Building Machine Learning Applications With Streamlit! This project is designed embed a machine learning file into an app for users. It's uses a previously trained time series model(Prophet).

📖 Table of Contents

• Installation
• Usage
• Authors
• Acknowledgement
• contact

🔧 Installation

To get started , follow these installation steps:

# setup the environment on windows by running the following code.
python -m venv venv; venv\Scripts\activate; python -m pip install -q --upgrade pip; python -m pip install -r requirements.txt  

#On Linux
python3 -m venv venv; source venv/bin/activate; python -m pip install -q --upgrade pip; python -m pip install -r requirements.txt 

The Two commands are of the same structure 1.Activate the python environment 2.Upgrade pip to it current version 3.install the requirements located in requirements.txt: You should be at the root of your env

🚀 Usage

To see how the app works, follow these instructions: 1.After setting up enviroment,activatig the environment, and installing requirments,type

streamlit run src/App.py #in the terminal

This will open the App in your browser

Deployment This app has been deployed on Streamlit cloud platform access it here

👥 Authors

This project is developed and maintained by:

• Sylvester Junior Ampomah
• Jacob Jaroya 🚀
• Kinsley Yaw Asiedu ⭐️
• Felix kiprotich 💡 Feel free to reach out to us with any questions or feedback!

✨ Acknowledgments

We would like to express our gratitude to The Azubi Africa team for their valuable contributions to this project.

📞 Contact

For any questions, concerns, or suggestions regarding this project, please contact us at sylvesterjnr87@gmail.com.