Rain Prediction in Australia using Machine Learning Ensemble Models

Here is the professional presentation of your project in English, formatted perfectly for GitHub, a portfolio, or LinkedIn.

1. Project Title

Rainfall Prediction in Australia using Ensemble Machine Learning

2. Project Description

This project focuses on building a robust predictive model to determine whether it will rain tomorrow in Australia based on historical daily weather observations from various locations.

The workflow involves an extensive End-to-End Machine Learning pipeline:

Data Cleaning: Handling missing values using sophisticated imputation techniques and managing outliers.

Feature Engineering: Encoding categorical variables and scaling numerical features for optimal model performance.

Class Imbalance: Addressing the skewed nature of weather data (rainy days vs. sunny days) using techniques like SMOTE.

Modeling: Leveraging high-performance algorithms including Logistic Regression, Random Forest, and XGBoost.

Optimization: Implementing a Voting Classifier (Ensemble Method) to combine the strengths of different models, resulting in superior accuracy and reliability.