What is Machine Learning?

Machine learning is a subfield of artificial intelligence (AI) that focuses on developing algorithms and statistical models that enable computers to learn from and make predictions or decisions based on data. Rather than being explicitly programmed to perform a specific task, machine learning systems use patterns and inference to improve their performance on tasks over time.

Here are some key aspects of machine learning:
Data: Machine learning relies heavily on data. The quality and quantity of data significantly impact the performance of machine learning models.

Algorithms: These are the methods used to analyze data, identify patterns, and make predictions. Common algorithms include decision trees, neural networks, and support vector machines.

Training: The process of teaching a machine learning model by feeding it data. During training, the model learns to identify patterns and relationships in the data.

Model: A trained machine learning algorithm that can make predictions or decisions based on new data.

Features: The individual measurable properties or characteristics of the data used for making predictions.

Supervised Learning: A type of machine learning where the model is trained on labeled data, meaning the data includes both the input and the desired output.

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What is Machine Learning?