Pre-Modeling: Data Preprocessing and Feature Exploration in Python
April Chen
http://mdp.cdm.depaul.edu/DePy2016/default/schedule
Data preprocessing and feature exploration are crucial steps in a modeling workflow. In this tutorial, I will demonstrate how to use Python libraries such as scikit-learn, statsmodels, and matplotlib to perform pre-modeling steps. Topics that will be covered include: missing values, variable types, outlier detection, multicollinearity, interaction terms, and visualizing variable distributions. Finally, I will show the impact of utilizing these techniques on model performance. Interactive Jupyter notebooks will be provided.
Видео Pre-Modeling: Data Preprocessing and Feature Exploration in Python канала Next Day Video
http://mdp.cdm.depaul.edu/DePy2016/default/schedule
Data preprocessing and feature exploration are crucial steps in a modeling workflow. In this tutorial, I will demonstrate how to use Python libraries such as scikit-learn, statsmodels, and matplotlib to perform pre-modeling steps. Topics that will be covered include: missing values, variable types, outlier detection, multicollinearity, interaction terms, and visualizing variable distributions. Finally, I will show the impact of utilizing these techniques on model performance. Interactive Jupyter notebooks will be provided.
Видео Pre-Modeling: Data Preprocessing and Feature Exploration in Python канала Next Day Video
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