Machine Learning Tutorials
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 […]
Unsupervised Learning Unsupervised Learning is a type of Machine Learning where a model learns patterns from data without any labeled examples without any guidance. Unlike supervised learning, where the model is trained using input-output pairs, unsupervised learning finds hidden structures and relationships in the data on its own. How Unsupervised Learning works? In Unsupervised learning, […]
Supervised Learning Supervised Learning is a type of Machine Learning where a model learns from labeled data.In this method the model is trained with labeled datasets. This means that the model is provided with input-output pairs, where the input data has corresponding correct outputs. How Supervised Learning Works? Supervised Learning involves training a model using a […]