Data analytics examines data sets to conclude the information they contain. This process is typically performed with specialized software and tools. Data analytics is crucial for businesses and organizations because it provides insights to drive better decision-making, improve efficiency, and gain a competitive edge.

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Machine learning (ML) is a subset of artificial intelligence (AI) that involves the development of algorithms that enable computers to learn from and make predictions or decisions based on data. Instead of being explicitly programmed for every task, ML algorithms build models based on sample data, known as training data, to make data-driven predictions or decisions.

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Data analytics examines data sets to draw conclusions about the information they contain. This process is typically performed with specialized software and tools. Data analytics is crucial for businesses and organizations because it provides insights to drive better decision-making, improve efficiency, and gain a competitive edge.

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Machine learning (ML) is a subset of artificial intelligence (AI) that involves the development of algorithms that enable computers to learn from and make predictions or decisions based on data. Instead of being explicitly programmed for every task, ML algorithms build models based on sample data, known as training data, to make data-driven predictions or decisions.

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Software testing is a critical process in developing software applications to identify and rectify software defects, bugs, or errors. The primary objective of software testing is to ensure that the software meets its intended requirements, functions correctly, and delivers a satisfactory user experience. By systematically examining the software, testers can help enhance its quality, reliability, and performance.

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