AI-MLite

The Power of Machine Learning: Transforming Businesses

Understanding ML

The "machine learning" subfield of artificial intelligence concerns the models and techniques that allow computers to learn and form judgments or predictions without being explicitly programmed. Data patterns are found using ML algorithms, which improve with practice. Businesses may now promptly analyze Large volumes of data to uncover hidden trends and generate insightful information.

Six reasons why XGBoost is better than GBM

XGBoost (eXtreme Gradient Boosting) and GBM (Gradient Boosting Machine) are both popular machine-learning algorithms for classification and regression problems.

Here are some reasons why XGBoost is considered better than GBM:

1. Regularization: XGBoost has a regularization term in its objective function, which penalizes models for being too complex, thus reducing overfitting. GBM does not have this feature.