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.

• 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