图 书 馆
贝叶斯推理Bayesian Inference |
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| 课程网址: | http://videolectures.net/mlss2011_green_bayesian/ |
| 主讲教师: | Peter Green |
| 开课单位: | 布里斯托尔大学 |
| 开课时间: | 2011-10-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Inference is the process of discovering from data about mechanisms that may have caused or generated that data, or at least explain it. The goals are varied - perhaps simply predicting future data, or more ambitiously drawing conclusions about scientific or societal truths. In the language of applied mathematics, these are inverse problems. Bayesian inference is about using probability to do all this. One of its strengths is that all sources of uncertainty in a problem can be simultaneously and coherently considered. It is model-based (in the language of machine learning, these are generative models), and we can use Bayesian methods to choose and criticize the models we use. |
| 关 键 词: | 社会真理; 应用数学; 贝叶斯方法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-23：cwx |
| 阅读次数: | 150 |