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Pandas_notes: The note for Pandas is based on contents from Kaggle courses.
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sklearn_note: The note contains some useful contents for machine learning.
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Numpy_notes: The note is made by contents met during the competition.
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main: It includes ten features:
- electronegativity (both atoms) [mean, std, min, max]
- radius (both atoms) [mean, std, min, max]
- bond angles
- pi bonds (both atoms) [mean, std, min, max]
- hybridization (both atoms) [mean, std, min, max]
- distance [mean, std]
- position (both atoms) [x, y, z]
This is the main file of the competition. It consists of several steps:
- Loading of data
- Data pre-processing
- Model selection
- Training
- Prediction
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Predicting scalar coupling constant with machine learning especially XGBoost and LightBoost.
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