《深度学习》花书学习第一周

深度学习第一周
一、学习内容
------------------------------------------------------------------------------7月29日起
5.1学习算法································87
5.2容量、过拟合和欠拟合····················97
5.3超参数和验证集··························105
5.4估计、偏差和方差························107
5.5最大似然估计····························115
5.5贝叶斯统计······························118
5.6监督学习算法····························122
5.8无监督学习算法··························128
-------------------------------------------------------------------------------8月4日看完
二、学习目标
1.明确概念：经验，任务，性能度量
2.什么是过拟合、欠拟合，分别是什么现象，发生这个问题的原因，如何解决
3.了解最大似然，贝叶斯学习，先验和后验什么含义。
4.明确概念：监督学习和无监督学习。包含哪些算法（算法大体了解即可，以后用到再仔细学）
5.练习：数据拟合

三、思维导图