📊 DATASETS USED IN MACHINE LEARNING

🤖 Introduction to Machine Learning Datasets

A dataset is a structured collection of data used by Machine Learning algorithms to learn patterns, relationships, and useful information from examples. Datasets are the foundation of almost every Machine Learning project.

In Machine Learning, datasets generally contain features (input variables) and a target variable (output). Features provide the information used by a model, while the target represents the value that a supervised learning model attempts to predict.

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Features

Input variables or attributes used by a Machine Learning model to learn patterns from the data.

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Target

The output variable that a supervised Machine Learning model attempts to predict.

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Data Preparation

Data may require cleaning, transformation, encoding, scaling, and feature selection before model training.

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Model Training

Machine Learning algorithms use training data to identify patterns and build predictive models.

💡 Explore the datasets below to study different Machine Learning problems such as classification, regression, clustering, dimensionality reduction, and feature selection.

📊 DATASETS USED IN MACHINE LEARNING

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