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Deep learning is machine learning, and machine learning is artificial intelligence. But how do they fit together (and how do you get started learning)? Read on to find out.

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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