课程大纲
概率 (3.5h)
- 概率的定义
- 二项分布
- 日常使用练习
Statistics (10.5小时)
- 描述性 Statistics
- 推理 Statistics
- 回归
- 逻辑回归
- 习题
Programming简介(3.5h)
- 程序 Programming
- 功能性 Programming
- 哎呀 Programming
- 练习(为选择的游戏编写逻辑,例如无球和十字架)
Machine Learning (10.5小时)
- 分类
- 聚类
- Neural Networks
- 练习(为选择的电脑游戏编写 AI)
规则引擎和专家系统(7 小时)
- 规则引擎简介
- 为同一游戏编写 AI,并将解决方案结合到混合方法中
要求
- 没有。本课程将解释概率和统计等所有概念。如果您已经熟悉概率和统计学,请参考我们的课程代码 aiint。
观众
- 对学习人工智慧 Machine Learning 和程式设计感兴趣的初学者
客户评论 (5)
节奏很好,知识分享、演示和实际工作很好地融合在一起。 菲利普非常有吸引力,并提供了完成课程的能量。 有很多 1:1 的教学是件好事,菲利普进行了个人训练练习。
Colin - Worldpay
课程 - BPMN, DMN, and CMMN - OMG standards for process improvement
机器翻译
The training definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide. It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.
Terry Strachan - Exel Computer Systems plc
课程 - OptaPlanner in Practice
Shared examples of every function and/or operators are all well explained.
Brian Amlon - Thakral One, Inc.
课程 - Introduction to Drools 7 for Developers
a lot of practices are very welcome, many try and learn cases are embedded
Nadia Ivaniuk - Credit Suisse (Poland) Sp.z o.o.
课程 - Modelling Decision and Rules with OMG DMN
Exercises and solving problems in groups when the problems were more difficult.