Artificial Intelligence
K-Means Clustering Algorithm K-Means is one of the most popular unsupervised machine learning algorithms used for clustering. It is used to group similar data points into clusters based on their features. The algorithm attempts to minimize the variance within each cluster, ensuring that data points within the same cluster are as close as possible while […]
Types of Unsupervised Learning Machine Learning is a branch of Artificial Intelligence that enables computers to learn from data and make decisions without being explicitly programmed. There are two main types of learning: Supervised and Unsupervised. In this article, we will focus on Unsupervised Learning. What is Unsupervised Learning? Unsupervised Learning is a type of […]
Types of Boosting in Machine Learning Boosting is a powerful ensemble learning technique in machine learning that combines multiple weak models to create a strong predictive model. It improves accuracy by sequentially training models and correcting previous errors. Boosting is widely used in various applications, including classification and regression tasks. The different types of Boosting […]
Ensemble Machine Learning Ensemble Machine Learning is a technique where multiple models are combined to improve the overall performance of a machine learning system. Instead of relying on a single model, ensemble methods use multiple models to make better predictions by reducing errors and increasing accuracy. Why Use Ensemble Learning? Individual models may have limitations, […]
Data Preprocessing Libraries in Python Data preprocessing is a crucial step in Machine Learning that involves cleaning, transforming, and organizing raw data into a suitable format for analysis. Real-world data is often incomplete, inconsistent, or contains errors, making preprocessing essential for improving the performance of machine learning models. What is Data Preprocessing? Data preprocessing is […]
Machine Learning Activities Machine Learning (ML) is a branch of Artificial Intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. ML models go through several key activities to ensure they function effectively. These activities include data collection, data preprocessing, model selection, model training, and evaluation. Data Collection Data […]