Supervised learning in machine learning explained | TECH Global University
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3 categories of machine learning you should understand 💡 1. Supervised learning: The algorithm learns from labeled historical input and output data to create a model that can make predictions. Common algorithms include neural networks, decision trees, linear regression, and support vector machines. Used for tasks like sales forecasting, fraud detection, and predicting equipment failure. 2. Unsupervised learning: The algorithm finds patterns in unlabeled data to group data points into clusters.
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TikToktiffintech
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Want to understand Supervised Learning in minutes? 🚀 This is one of the simplest explanations you’ll find perfect for beginners stepping into Machine Learning and AI. In this video, I break down supervised learning with clear, real-world examples so you can finally understand how machines learn from labeled data and make accurate predictions. If AI, Machine Learning, or Data Science is your future start here. 💬 Comment “Supervised Done” if you want more AI content. 🔔 Follow for advanced conce
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