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分类于: 人工智能 计算机基础
简介
A Course in Machine Learning 豆 0.0分
资源最后更新于 2020-09-27 15:05:53
作者：Hal Daumé III
出版社：
出版日期：0000-01
ISBN：9781439824122
文件格式： pdf
标签： 机器学习 ML 人工智能 ebook MachineLearning 方法 Computer AI
简介· · · · · ·
Machine learning is the study of algorithms that learn from data and experience. It is applied in a vast variety of application areas, from medicine to advertising, from military to pedestrian. Any area in which you need to make sense of data is a potential consumer of machine learning.
CIML is a set of introductory materials that covers most major aspects of modern machine lea...
目录
0. Front Matter
1. Decision Trees
2. Geometry and Nearest Neighbors
3. The Perceptron
4. Machine Learning in Practice
5. Beyond Binary Classification
6. Linear Models
7. Probabilistic Modeling
8. Neural Networks
9. Kernel Methods
10. Learning Theory
11. Ensemble Methods
12. Efficient Learning
13. Unsupervised Learning
14. Expectation Maximization
15. Semi-Supervised Learning
16. Graphical Models
17. Online Learning
18. Structured Learning
19. Bayesian Learning
20. Back Matter
1. Decision Trees
2. Geometry and Nearest Neighbors
3. The Perceptron
4. Machine Learning in Practice
5. Beyond Binary Classification
6. Linear Models
7. Probabilistic Modeling
8. Neural Networks
9. Kernel Methods
10. Learning Theory
11. Ensemble Methods
12. Efficient Learning
13. Unsupervised Learning
14. Expectation Maximization
15. Semi-Supervised Learning
16. Graphical Models
17. Online Learning
18. Structured Learning
19. Bayesian Learning
20. Back Matter
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