教师信息
- 教师姓名:骆威
- 所属院系:数学与信息学院(软件学院)
- 个人简介:
课程信息
- 课程所属院系:管理科学与工程系
- 选课学生数:150
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- 课程题库试题:题
- 课程卷库试卷:张
- Lecture 1: Introduction
- Lecture 2: linear regression with one variable
- Lecture 3: linear regression with multiple variables
- Lecture 4: logistic regression
- Lecture 5: regularization
- Lecture 6: neural networks: representation
- Lecture 7: neural networks: learning
- Lecture 8: Advice for applying machine learning
- Lecture 9: machine learning system design
- Lecture 10: support vector machine
- Lecture 11: clustering
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Lecture 12: dimensionality reduction
- 12.1: motivation I - data compression
- 12.2: motivation II - visualization
- 12.3: principal component analysis problem formulation
- 12.4: principal component analysis algorithm
- 12.5: choosing the number of principal components
- 12.6: reconstruction from compressed representation
- 12.7: advice for applying PCA
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Lecture 13: anomaly detection
- 13.1: problem motivation
- 13.2: guassian distribution
- 13.3: algorithm
- 13.4: developing and evaluating an anomaly detection system
- 13.5: anomaly detection vs. supervised learning
- 13.6: choosing what features to use
- 13.7: multivariate gaussian distribution
- 13.8: anomaly detection using the multivariate gaussian distribution
- Lecture 14: recommender system
- Lecture 15: large-scale machine learning
- Lecture 16: application examples