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Answer :
AI, ML, and DL are related fields in technology, and here's how they differ:
Artificial Intelligence (AI):
- What: AI refers to the broader concept of machines or systems being able to perform tasks that normally require human intelligence. This can include recognizing speech, making decisions, problem-solving, and translating languages.
- How: AI works through algorithms that enable machines to mimic human-like behaviors.
- Why: The goal of AI is to create systems that can function intelligently and independently.
Machine Learning (ML):
- What: ML is a subset of AI. It involves training algorithms on data so that they can learn to make decisions or predictions.
- How: ML uses statistical techniques to help machines improve their performance on a task over time, based on experience.
- Why: ML is important because it allows machines to learn from data without being explicitly programmed for every task.
Deep Learning (DL):
- What: DL is a further specialization within ML. It uses neural networks with many layers (hence 'deep') to analyze various factors of data.
- How: DL mimics the human brain with networks of neurons, enabling it to learn from vast quantities of data.
- Why: It's especially useful for complex tasks like image and speech recognition.
In summary, think of AI as the overall goal of creating intelligence in machines, ML as a way for machines to learn from data to achieve better AI, and DL as a more advanced method within ML for processing large data sets and complex tasks.
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