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How does Machine Learning work? What is Artificial Intelligence (AI)?

Machine Learning (ML) works by teaching computers to recognize patterns and make decisions based on data.

Here is a simple explanation that shows the steps involved in Machine Learning:

Data Collection: First, we gather lots of data about whatever we are trying to teach the computer. This could be anything from pictures of cats to information about how people drive cars.

Training: Next, we use this data to train the computer. We show it examples and tell it what we want it to learn. For example, we might show it lots of pictures of cats and tell it, "These are cats."

Learning: The computer uses algorithms to analyze the data and look for patterns. It learns from the examples we give it and starts to understand what cats look like.

Prediction: Once the computer has learned from the training data, we can give it new data that it has not seen before, like a picture of a new cat. The computer uses what its learned to make predictions or decisions, like saying, "Yes, this is a cat."

Feedback and Improvement: As the computer makes predictions, we can give it feedback to help it improve. If it makes a mistake, we can correct it, and the computer can learn from that feedback to get better over time.

Once a machine learning model is trained on a dataset and has learned to make accurate predictions, it can be integrated into broader AI systems to perform specific tasks such as NLP (Natural Language Processing) and others.

Artificial Intelligence (AI): AI is a broad field of computer science that aims to create systems or machines that can perform tasks that typically require human intelligence. This includes things like reasoning, problem-solving, understanding natural language and recognizing patterns.

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