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  - lucazsh/RadNet
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  ---
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  RadNet it is composed of 2 LSTM (Long-Short Term Memory) layers that helps the model to ident), which will facilitate the prediction of the daily radiation amount as well as solar storms in LEO (Low Earth Orbit). This model was also featured by the National Space Society (NSS) under the project Aletheia.
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  The radiation data was extracted from the NASA OSDR EDA API (https://visualization.osdr.nasa.gov/eda/), from the RR's missions (RR-1, RR-3, RR-4, RR-6, RR-8, RR-9, RR-12, RR-17, and RR-19).
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  Below is a Python code that runs the AI and displays the daily radiation dose and solar storm:
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  ```
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  import json
 
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  - lucazsh/RadNet
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  ---
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+ ## Introduction:
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  RadNet it is composed of 2 LSTM (Long-Short Term Memory) layers that helps the model to ident), which will facilitate the prediction of the daily radiation amount as well as solar storms in LEO (Low Earth Orbit). This model was also featured by the National Space Society (NSS) under the project Aletheia.
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  The radiation data was extracted from the NASA OSDR EDA API (https://visualization.osdr.nasa.gov/eda/), from the RR's missions (RR-1, RR-3, RR-4, RR-6, RR-8, RR-9, RR-12, RR-17, and RR-19).
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+ ## Installation:
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+
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+ Make sure you have Python 3.10+ installed on your system. If not, you can download it from [python.org](https://www.python.org/).
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+ Install dependencies:
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+ ```bash
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+ pip install numpy json torch
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+ ```
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+
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+ ## Code:
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+
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  Below is a Python code that runs the AI and displays the daily radiation dose and solar storm:
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  ```
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  import json