Feature Engineering
Winsorization: Handling Outliers in Machine Learning
Handle outliers with Winsorization, a powerful data preprocessing technique. Includes Python code examples.
A Comprehensive Guide to Complete Case Analysis
Learn Complete Case Analysis (CCA) for handling missing data in machine learning, including advantages and...
How to Detect Outliers in Python: A Comprehensive Guide
Learn to detect outliers in Python. We discuss outlier detection and handling methods using Python...
Multiple Imputation with Chained Equations (MICE) – what is it?
Discover what MICE (multivariate imputation of chained equations) is, and how to apply it with...
KNN imputation of missing values in machine learning
KNN imputation is a simple imputation technique to replace missing data for machine learning while...
Your Guide to Missing Values Imputation
Find out more about missing values, how they appear in the data, and how you...
Target Encoder: A powerful categorical encoding method
Target encoder is Python implementation of the target encoding method for highly cardinal categorical variables....
Imputing missing data with Scikit-learn’s simple imputer
Implement the most common missing value imputation methods, like mean, median, and most frequent imputation...
Feature scaling in machine learning: Standardization, MinMaxScaling and more…
Discover why and how we scale variables in Python for machine learning.
Master Data Binning in Python using Pandas
Find out what data binning is, why we do it, and how to implement it...
Unlock Data’s Potential: A Step-by-Step Data Transformation Guide
Data is the lifeblood of any organization. But not in its raw state. Data transformation...
Mastering data preprocessing: Techniques and best practices
Discover how to preprocess your data to make it suitable for machine learning.
One-hot encoding categorical variables
Discover different variants of one hot encoding, including encoding of specific or frequent categories, and...
Data discretization in machine learning
Why and how should we discretize data in machine learning.
Variance stabilizing transformations in machine learning
The logarithm, power, and square root are variance stabilizing transformations. How and why are they...
Feature engineering for machine learning: What is it?
Discover different methods for feature engineering for machine learning, what their advantages and limitations are,...