Feature Selection and Feature Engineering

An educational talk about Feature Selection and Feature Engineering and why it matters.

What this education talk is

• an introduction to why feature selection is an essential step in building DS and ML pipelines.
• an introduction to basic feature engineering.

What this education talk is NOT

• an exhaustive guide to feature engineering.
• a one-fits-all solution guide.

Objective of this education talk

establish an intuition about where to focus efforts when creating DS and ML pipelines.
(assuming a dataset post preparation and cleaning steps is available)

Modules and Materials Collection

Note: the content of this education talk is also being used in presentations.

Slides

slide deck used in the presentations and video materials

Jupyter Notebooks

used in the presentations and video materials.
Note: these notebooks have been developed using older versions of packages (particularly scikit-learn). They have not been verified with current versions.

Demo Notebook Feature Selection
Demo Notebook Feature Engineering

Dataset

Madelon Dataset paper
Design of experiments for the NIPS 2003 variable selection benchmark Isabelle Guyon – July 2003
Copy of the Dataset

Algorithms

Boruta Feature Selection Heuristic
Feature Selection with the Boruta Package
Miron B. Kursa (University of Warsaw)
Witold R. Rudnicki (University of Warsaw)

Videos

1. Overview
2. Feature Selection
3. Feature Selection notebook
4. Feature Engineering
5. Feature Engineering notebook
6. Remarks and Results

Back to Saravji’s Hut

Back to Data Science and Machine Learning

Terms of use

Terms as outlined on main page are applicable.

License

These materials are governed by the BSD-3 license. Details