🌧️ Rainfall Prediction using Machine Learning

This project predicts rainfall using machine learning techniques in Python. It uses weather data such as temperature, humidity, wind speed, and pressure to train models like Logistic Regression, Decision Tree, and Random Forest for forecasting rainfall occurrence or amount.

📌 Features

• Preprocessing and cleaning of weather dataset
• Exploratory Data Analysis (EDA) with visualizations
• Implementation of multiple ML algorithms
• Model evaluation using accuracy, precision, recall, and F1-score
• Easy-to-use prediction system for rainfall forecasting

🛠️ Tech Stack

• Language: Python
• Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn

📊 Workflow

1. Data Collection & Cleaning
2. Exploratory Data Analysis (EDA)
3. Feature Engineering & Preprocessing
4. Model Training & Hyperparameter Tuning
5. Model Evaluation & Results Visualization
6. Prediction

🚀 Installation & Usage

1. Clone the repository:

   git clone https://github.com/SrijayaSarkar/Rainfall_Prediction_using_Machine_learning.git
   cd Rainfall_Prediction_using_Machine_learning