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Machine Learning

Machine learning is a part of Artificial Intelligence (AI) that helps computers learn from experience. Instead of being told exactly what to do, the computer looks at data and figures out patterns or makes decisions on its own. For example, it can learn to recognize faces, suggest movies, or predict the weather just by analyzing lots of information. Machine learning is used in many things we use every day, like search engines, voice assistants, and social media.

Courses

Machine Learning Pipeline – the step-by-step process of preparing data—like cleaning it and organizing it—so a computer can learn from it and make predictions.
Supervised Learning – teaches a computer by showing it examples with the correct answers, like showing photos labeled “cat” or “dog” so it can learn to tell the difference on its own.
Unsupervised Learning – helps a computer find patterns in data without giving it the answers first—like grouping similar customers or finding hidden trends.
Reinforcement Learning – the computer learns what actions get good results by trying things and getting feedback over time.
Semi-Supervised Learning – uses a small amount of labeled data and a lot of unlabeled data to help the computer learn faster when we don’t have all the answers.
Deployment of ML Models – putting the information learned into the real world—like on a website or app—so people can use it to make predictions or decisions in real time.
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8th Grade

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High School Junior

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