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Feature Engineering: Some Towarddatascience Tutorials

posted Sep 14, 2019, 8:53 PM by MUHAMMAD MUN`IM AHMAD ZABIDI   [ updated Sep 14, 2019, 9:48 PM ]
 

Six Important Steps to Build a Machine Learning System

A field guide to thinking about ML projects by Rahul Agarwal.

These are the 6 steps:

    1. Problem Definition
    2. Data
    3. Evaluation
    4. Features
    5. Modeling
    6. Experimentation

The Hitchhiker's Guide to Feature Extraction

Some tricks and code for Kaggle and everyday work by Rahul Agarwal.

Two interesting approaches:
  • Automatic feature creation using featuretools framework
  • Using autoencoders
 

The Five Feature Selection Algorithms every Data Scientist should know

By Rahul Agarwal.

These are the 5 algorithms:

    1. Pearson correlation
    2. Chi-squared
    3. Recursive feature elimination
    4. Lasso from sklearn
    5. RandomForest from sklearn
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