https://github.com/sahar-dev/weather

Predict next-day rainfall in Australia using machine learning and MLOps.
https://github.com/sahar-dev/weather

dvc-for-data-science fastapi machine-learning mlops

Last synced: 7 days ago
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Predict next-day rainfall in Australia using machine learning and MLOps.

• Host: GitHub
• URL: https://github.com/sahar-dev/weather
• Owner: Sahar-dev
• Created: 2023-12-02T18:39:12.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-24T19:24:08.000Z (12 months ago)
• Last Synced: 2024-11-09T07:16:00.589Z (2 months ago)
• Topics: dvc-for-data-science, fastapi, machine-learning, mlops
• Language: Jupyter Notebook
• Homepage:
• Size: 11.9 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Rainfall Prediction MLops Project

Predict next-day rainfall in Australia using machine learning and MLOps using [Kaggle dataset]( https://www.kaggle.com/datasets/jsphyg/weather-dataset-rattle-package)

## Features

- Data Cleaning

- Feature Selection

- Model Training

- Keeping track of the models using MLFlow

- API with FastAPI

- Frontend with Streamlit

- Dashboard with Streamlit, HTML, and PowerBI

- Testing with DeepCheck

## Setup

1. **Backend API:**

   ```bash

   uvicorn main:app --host 0.0.0.0 --port 8000 --reload

2. **Frontend**

   ```bash

   streamlit run frontend/main.py

## Additional Components

1. Dashboard:

Utilizes Streamlit, HTML, and PowerBI.

2. Testing:

DeepCheck testing integrated.

## Roadmap

Dockerization and Automation with Jenkins (Coming Soon)