图 书 馆
统计机器学习导论Introduction to Statistical Machine Learning |
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| 课程网址: | http://videolectures.net/mlss08au_hutter_isml/ |
| 主讲教师: | Marcus Hutter |
| 开课单位: | IDSIA公司 |
| 开课时间: | 2008-03-11 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The first part of his tutorial provides a brief overview of the fundamental methods and applications of statistical machine learning. The other speakers will detail or built upon this introduction. Statistical machine learning is concerned with the development of algorithms and techniques that learn from observed data by constructing stochastic models that can be used for making predictions and decisions. Topics covered include Bayesian inference and maximum likelihood modeling; regression, classification, density estimation, clustering, principal component analysis; parametric, semi-parametric, and non-parametric models; basis functions, neural networks, kernel methods, and graphical models; deterministic and stochastic optimization; overfitting, regularization, and validation. |
| 关 键 词: | 统计机器; 观察数据; 贝叶斯推理 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-05-14：yumf |
| 阅读次数: | 158 |