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Understanding a data

“Understanding Data in Machine Learning”, especially suitable for a YouTube study channel like ThinkRise: Data is the foundation of machine learning, and understanding it is the first step toward building intelligent models. In this topic, we explore what data is, how it is collected, and why its quality matters more than quantity. You’ll learn about different types of data such as structured, unstructured, and semi-structured data, along with numerical and categorical features. We’ll also cover how data is represented, common data formats, and the importance of cleaning and preprocessing before training a model. This lesson explains key concepts like features, labels, datasets, missing values, outliers, and data distributions in a simple and practical way. By understanding your data properly, you can make better decisions, improve model accuracy, and avoid common machine learning mistakes. Whether you’re a beginner or revising core concepts, this video helps you build a strong foundation in machine learning by teaching you how to think critically about data before applying algorithms.