机器学习总结

Machine learning is a theoretical approach that allows machines to learn and improve intelligence. It can also be applied practically with the use of data, features, and models. However, there are several actions involved in this process, such as data collection and feature selection. The speaker also mentions that statistical methods and data predictions can sometimes fail, and the reasons for these failures. 最后我们总结一下机器学习 机器学习是一种理论 让机器能够学习 并且在学习中提高智能 同时呢 机器学习又是一种可以落地的方法 数据特征模型是构成这个机器学习落地的最核心的三个要素 当然也包含了串联这三个要素的好多action 包括数据收集呀 特征选择等等等等 并且我们用了一个例子 串联了所有也学习到了程度 统计方式以及数据预测可能会失败 以及失败的原因