Boost your machine learning skills
Master advanced techniques and become the machine learning expert companies are desperate to hire.
Class Imbalance in Machine Learning
Contrary to what you’ll read online or get from ChatGPT, class imbalance is NOT the problem. How you handle it is.
Confusion Matrix, Precision, and Recall
Find out what the confusion matrix is and how it relates to other classification metrics like precision, recall and f1-score.
Multiple Imputation with Chained Equations (MICE) – what is it?
Discover what MICE (multivariate imputation of chained equations) is, and how to apply it with Python to impute missing data.
KNN imputation of missing values in machine learning
KNN imputation is a simple imputation technique to replace missing data for machine learning while preserving the variable distribution.
Your Guide to Missing Values Imputation
Find out more about missing values, how they appear in the data, and how you can replace them with unbiased estimates for machine learning.
Target Encoder: A powerful categorical encoding method
Most machine learning models don't natively handle...
Advanced Machine Learning Projects for data science
Machine learning and artificial intelligence are the most...
Leveraging Data Science for Finance
In this article, I share my experience about leveraging data science for finance while working in a fintech company.
Imputing missing data with Scikit-learn’s simple imputer
Implement the most common missing value imputation methods, like mean, median, and most frequent imputation with sklearn’s simple imputer.
Data Science Prerequisites: The Door to Data Mastery
Discover the data science prerequisites that’ll smooth your transition into this fascinating field that combines technical with soft skills.