Data Science Pipeline

in costruzione

OSEMN (Data Science is Awesome)

1. Environment
   1. Libraries
   2. Custom functions
2. Obtaining data
3. Scrubbing data (loop 3-4-5)
   1. Errors
   2. Missing data
4. Exploring data (loop 3-4-5)
   1. Exploratory Data Analysis
   2. Feature engineering
   3. Feature selection
5. Modeling data (loop 3-4-5)
   1. Estimation
   2. Evaluation
   3. Benchmarks
6. iNterpreting data
   1. Business insights
   2. Data visualization

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