该参考描述所示目录。请向院校确认当前的招生项目及适用于您入学年的条件。
描述
机器学习 基本的机器学习技术，强调使用这些技术设计并实现小型实用学习系统。主题包括将学习视为搜索、归纳偏好、概念学习、计算学习、基于解释的学习与强化学习。讲座与研讨，每周 3 小时。先修课程：COSC 3P71（最低 60%）。注：该课程可能以多种授课方式提供。授课方式将在学期课程表中列出。
先修课程
- 先修课程：COSC 3P71（最低 60%）。
条件与方式
- 先修课程：COSC 3P71（最低 60%）。
- 注：本课程可能以多种授课方式开设。授课方式将在适用学期的学术课程表中列出。
原文参考文本
Machine Learning Fundamental machine learning techniques with emphasis on using these techniques to design and implement small practical learning systems. Topics include learning as a search, inductive bias, concept learning, computational learning, explanation-based learning and reinforcement learning. Lectures, seminar, 3 hours per week. Prerequisite(s): COSC 3P71 (minimum 60 percent). Note: this course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.
- Prerequisite(s): COSC 3P71 (minimum 60 percent).
- Note: this course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.
来源与参考
为帮助您核实信息，保留了日期和来源。为便于阅读提供了翻译；以官方来源为准，查看条件和要求。
来源参考 : https://brocku.ca/webcal/2024/undergrad/cosc.html