Скачать или смотреть ENSEMBLE LEARNING IN ML|MACHINE LEARNING|SNS INSTITUTIONS

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Ensemble learning is a powerful technique in machine learning where multiple models, often called "learners," are combined to solve a problem and improve overall performance. In this video, we explore the core concepts of ensemble learning, including why and how combining models like decision trees, support vector machines, or neural networks can lead to better accuracy and generalization. You'll learn about popular ensemble methods such as Bagging, Boosting, and Stacking, with real-world examples and visual explanations to make these concepts easy to understand. Whether you're a beginner or looking to deepen your ML knowledge, this video will give you a solid foundation in one of the most effective strategies for building robust predictive models.