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Neural networks explained: Machine learning made easy

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Neural networks explained: Machine learning made easy

Confused by neural networks? This video breaks it all down in simple terms. Understand how they work and why they’re at the core of modern machine learning. #MachineLearning #NeuralNetworks #AIExplained

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AI The Revolution

Types of Machine Learning (ML) Systems: 1. Based on Learning Style: a. Supervised Learning Learns from labeled data. Goal: Predict output for new inputs. Common tasks: Classification, Regression. Examples: Linear Regression, Decision Trees, SVM. b. Unsupervised Learning Learns from unlabeled data. Goal: Discover hidden patterns. Common tasks: Clustering, Dimensionality Reduction. Examples: K-Means, PCA, DBSCAN. c. Semi-Supervised Learning Uses a small amount of labeled data large unlabeled data.

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Types of Machine Learning (ML) Systems: 1. Based on Learning Style: a.

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