【陆勤读书】要点摘录(二)
陆勤读书:《Machine Learning With R》
1 机器学习应用于数据的步骤
第一步:收集数据 Collecting DATA
第二步:探索和准备数据 Exploring and preparing the DATA
第三步:对数据训练模型 Training a model on the DATA
第四步:评价模型性能 Evaluating model performance
第五步:改进模型性能 Improving model performance
2 A key early componet of any machine project involves managing and understanding the data you have collected.
3 Any learning algorithm is only as good as its input data, and in many cases, input data is complex, messy, and spread across multiple sources and formats.
4 Because of this complexity, the largest portion of effort invested in machine learning projects is spent on the data preparation and exploration process.
5 问题集
1)如何进行机器学习应用??
2)数据准备和探索怎么做??
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