Random Forests
Random Forests in Machine Learning 1. Introduction to Random Forests Random Forest is a Supervised Machine Learning algorithm that is used for both Classification and Regression tasks. It is an….
Random Forests in Machine Learning 1. Introduction to Random Forests Random Forest is a Supervised Machine Learning algorithm that is used for both Classification and Regression tasks. It is an….
Decision Trees in Machine Learning 1. Introduction to Decision Trees A Decision Tree is a Supervised Learning algorithm used for both classification and regression problems. It mimics human decision-making by….
Types of Machine Learning Machine Learning (ML) is classified into three main types: Each type has its own approach, methodologies, and applications. Below, we will explore them in detail, covering….
Principal Component Analysis (PCA) – A Comprehensive Guide Introduction to PCA Principal Component Analysis (PCA) is a powerful dimensionality reduction technique used in machine learning and data science. It transforms….
Dimensionality Reduction Techniques: A Comprehensive Guide Introduction Dimensionality reduction is a critical step in data preprocessing that helps improve the efficiency and performance of machine learning models by reducing the….
Handling Imbalanced Data in Machine Learning Introduction Imbalanced data occurs when the distribution of classes in a dataset is highly skewed, meaning one class has significantly more samples than the….
Data Encoding Techniques: One-Hot Encoding & Label Encoding Introduction to Data Encoding Data encoding is a crucial preprocessing step in machine learning, where categorical data is converted into a numerical….