Introduction to Machine Learning for Beginners (Part 1 of 17) | Machine Learning for Beginners
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Introduction to Machine Learning for Beginners (Part 1 of 17) | Machine Learning for Beginners
Welcome to the first lesson of our Machine Learning for Beginners course, presented by Bea Stollnitz, a Principal Cloud Advocate at Microsoft! Join us on this exciting journey to understand the fundamentals of classical machine learning and how it can be applied to solve real-world problems. In this introductory video, we cover: Motivation for ...
2023年11月13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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