Weather Prediction Project:-

This project is designed to predict weather conditions such as temperature, humidity, and precipitation based on historical weather data. The model utilizes machine learning techniques to forecast weather patterns and provide predictions for future dates.

Project Description:- The Weather Prediction Project aims to create a reliable weather forecasting system. This project includes:

Data preprocessing and feature engineering Training of machine learning models to predict weather Evaluation of model performance Visualizations for easy interpretation of results The goal is to develop a model that can predict weather parameters like temperature, humidity, and wind speed for the next few days.

Technologies Used:-

Python: The primary programming language used for the project. pandas: For data manipulation and analysis. NumPy: For numerical computing. Scikit-learn: For machine learning algorithms. Matplotlib/Seaborn: For data visualization. Jupyter Notebook: For interactive code development and presentation.

Dataset:- The dataset used for training the model includes historical weather data, which contains features such as:

Temperature (max, min, average) Humidity Wind Speed Rain Possibility The dataset is typically available from sources like Kaggle or can be collected via APIs like OpenWeatherMap.

Model Description The model used in this project could be a machine learning model such as:

Linear Regression for predicting numerical values like temperature. Decision Trees or Random Forests for training regression model.

PROJECT CREATOR :- AJAY BORA