Introduction to Machine Learning, Part 1: Machine Learning Fundamentals
2:37
mathworks.com
Introduction to Machine Learning, Part 1: Machine Learning Fundamentals
Explore the fundamentals behind machine learning, focusing on unsupervised and supervised learning. Learn about the common techniques, including clustering, classification, and regression.
2018年11月21日
短編
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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