https://github.com/rajspeaks/indian-rainfall-prediction-with-machine-learning-approach
Rainfall Analysis & Prediction in India using Machine Learning approach. This project was pre-trained model from where it has been reconstructed. It has been done under the mentor-ship of LinuxWorld Informatics Private Limited.
https://github.com/rajspeaks/indian-rainfall-prediction-with-machine-learning-approach
analysis data-science machine-learning machine-learning-algorithms machinelearning ml prediction-model rajdeep-das rajspeaks
Last synced: 6 months ago
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Rainfall Analysis & Prediction in India using Machine Learning approach. This project was pre-trained model from where it has been reconstructed. It has been done under the mentor-ship of LinuxWorld Informatics Private Limited.
- Host: GitHub
- URL: https://github.com/rajspeaks/indian-rainfall-prediction-with-machine-learning-approach
- Owner: Rajspeaks
- License: mit
- Created: 2021-12-11T09:37:48.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2022-05-03T10:17:58.000Z (over 3 years ago)
- Last Synced: 2025-02-09T22:46:49.547Z (8 months ago)
- Topics: analysis, data-science, machine-learning, machine-learning-algorithms, machinelearning, ml, prediction-model, rajdeep-das, rajspeaks
- Language: Jupyter Notebook
- Homepage:
- Size: 3.56 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Machine Learning approach to Indian Rainfall Prediction
This Project has been done under the mentorship of Linux World Informatics Private Limited.
## Gist About the Project:
In India, Rainfall or Monsoon is one of the great important factors of nature. Generally two types of predictions can be done for analyzing.
- Type 1- Long Term Predictions
- Type 2- Short Term Predictions
In this project, it is tried to analyze the Long Term rainfall using the collected datasets of Indian Meteorological Department. The aim is to predict the rainfall tendency in different areas by using the past data of those areas.
## Datasets:
- Dataset1([dataset1](https://data.gov.in/resources/district-rainfall-normal-mm-monthly-seasonal-and-annual-data-period-1951-2000))
- Average rainfall from 1951-2000 for each district, for every month.
- Dataset2([dataset2](https://data.gov.in/resources/subdivision-wise-rainfall-and-its-departure-1901-2015))
- Average rainfall for every year from 1901-2015 for each state.
## Technologies Used:
- Python
- Jupyter Notebook
- Above mentioned datasets.
## Conclusion:
Data observations are done into various visualization which helps in implementing the approximate outputs. In some cases, the machine learning didn’t work due to the fluctuations in rainfalls in some areas.
## Future Scope:
Helpful in Weather prediction and in understanding the rainfall sequences in different areas.
© Rajdeep Das