图 书 馆
机器学习Machine Learning |
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| 课程网址: | http://videolectures.net/deeplearning2016_precup_machine_learning... |
| 主讲教师: | Doina Precup |
| 开课单位: | 麦吉尔大学 |
| 开课时间: | 2016-08-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We provide a general introduction to machine learning, aimed to put all participants on the same page in terms of definitions and basic background. After a brief overview of different machine learning problems, we discuss linear regression, its objective function and closed-form solution. We discuss the bias-variance trade-off and the issue of overfitting (and the proper use of cross-validation to measure performance objectively). We discuss the probabilistic view of the sum-squared error as maximizing likelihood under specific assumptions on the data generation process, and present L2 and L1 regularization methods as priors from a Bayesian perspective. We briefly discuss Bayesian methodology for learning. Finally, we present logistic regression, the cross-entropy optimization criterion and its solution through first- and second-order methods. |
| 关 键 词: | 会起学习; 逻辑回归; 贝叶斯 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-22：yxd |
| 最后编审: | 2020-11-22：yxd |
| 阅读次数: | 27 |