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– Introduction
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Classroom Contents
Automating Supervised Machine Learning Pipeline Development
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- 1 – Introduction
- 2 – The highest level
- 3 – Supervised machine learning essence
- 4 – Features - Missing values
- 5 – Features - Data cleaning perception Vs reality
- 6 – Features - Encoding
- 7 – Features - Normalize
- 8 – Correlation - Methods
- 9 – Engineering features
- 10 – Human oversight
- 11 – Complete pipeline
