- Welcome to the Weather Data Analysis repository! This project is dedicated to the exploration and analysis of weather data using various data science techniques and tools.
- Weather data plays a crucial role in various fields such as agriculture, transportation, and climate research. Understanding historical weather patterns and trends can provide valuable insights for decision- making and planning.
Curated datasets of weather observations, including temperature, humidity, precipitation, wind speed, and other relevant parameters. These datasets may cover specific regions, time periods, or weather phenomena.
Jupyter notebooks and scripts for exploring and analyzing weather data. These notebooks demonstrate techniques for data cleaning, visualization, statistical analysis, and machine learning modeling.
Libraries and scripts for creating interactive and informative visualizations of weather data. Visualization is key to understanding complex patterns and trends in weather datasets.
Implementations of statistical models for forecasting weather conditions, anomaly detection, and trend analysis. These models leverage historical weather data to make predictions and identify unusual patterns.
Guides and examples for integrating weather data analysis pipelines into larger applications or systems. This may include APIs, web applications, or automated reporting systems.
Guidelines for contributing to the project, including instructions for dataset collection, analysis improvements, and new feature additions.
- Decision Tree
- NBC
- SVM
- ARIMA
- Name - Aatish Kumar Baitha
- M.Tech(Data Science 2nd Year Student)