Preprocessing and Pipelines | Supervised Machine Learning with scikit-learn
Learn how to impute missing values, convert categorical data to numeric values, scale data, evaluate multiple supervised learning models simultaneously, and build pipelines to streamline your workflow!
Datasets
https://drive.google.com/drive/folder...
Links
Python: https://www.python.org/downloads/
PyCharm: https://www.jetbrains.com/pycharm/dow...
scikit-learn: https://pypi.org/project/scikit-learn/
pandas: https://pypi.org/project/pandas/
numpy: https://pypi.org/project/numpy/
matplotlib: https://pypi.org/project/matplotlib/
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00:00 Course introduction
00:41 Chapter introduction
00:56 Preprocessing data
05:10 Handling missing data
08:26 Centering and Scaling
11:36 Evaluating multiple models
14:52 Congratulations