Last Updated on 12 months ago by School4Seo Team

Machine learning happens when computers analyze and recognize patterns in huge amounts of data, Machine learning means computers don’t need to be explicitly programmed or told what to do and Machine learning can become more efficient and accurate over time. These three statements about machine learning are true.

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• Machine learning will eventually develop to a level where it can replace advertisers entirely.
• Machine learning is a way of effectively summarizing large amounts of data.
• Machine learning happens when computers analyze and recognize patterns in huge amounts of data.
• Machine learning means computers don’t need to be explicitly programmed or told what to do.
• Machine learning can become more efficient and accurate over time.

The correct answers are: Machine learning happens when computers analyze and recognize patterns in huge amounts of data, Machine learning means computers don’t need to be explicitly programmed or told what to do and Machine learning can become more efficient and accurate over time.

Explanation: Machine learning means that computers don’t need to be explicitly programmed or told what to do. Instead, they can be trained to analyze and recognize patterns in huge amounts of data, learning as they go. Today, machine learning allows us to train a system with lots of junk email examples so that it can figure out patterns (“junk” or “not junk”) and become accurate over time (“this is probably junk”).

1. Machine learning happens when computers analyze and recognize patterns in huge amounts of data: This is the core definition. ML algorithms are designed to ingest vast datasets, identify correlations, trends, and structures within that data that might be imperceptible to humans.
2. Machine learning means computers don’t need to be explicitly programmed or told what to do: This is the distinguishing characteristic of machine learning compared to traditional programming. Instead of being given step-by-step instructions for every possible scenario, ML models “learn” from the data itself, adjusting their internal logic to achieve a goal.
3. Machine learning can become more efficient and accurate over time: This highlights the “learning” aspect. As an ML model is exposed to more data and receives feedback (e.g., whether a prediction was correct or not), it continuously refines its algorithms, leading to improved performance, greater accuracy, and increased efficiency in its tasks.