Machine Learning

This article explains Evaluation Metric on Machine Learning.

This article explains what Feature Engineering is, why it is important, and describes basic Feature Engineering techniques.

This article explains what One-Hot Encoding is on Machine Learning.

This article explains Label Encoding on Machine Learning.

This article explains what Stratified K-Fold Cross-Validation is on Machine Learning.

This article explains the concept of Random Search, one of the hyperparameter tuning methods to maximize the performance of models in machine learning, and introduce an example of implementation using the Scikit-learn library.

This article explains K-Fold Cross-Validation on Machine Learning.

One of the efficient methods to find the optimal parameters of a model in machine learning is Grid Search. This article explains what grid search is, how it works, and when it should be used.

This article explains what vectorization is on Machine Learning.

This article explains what Linear Regression with Multiple Variables is on Machine Learning.