课程: Machine Learning with Python: Foundations

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Normalizing your data

Normalizing your data - Python教程

课程: Machine Learning with Python: Foundations

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Normalizing your data

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- [Narrator] An ideal dataset is one that has no missing values and has no values that deviate from the expected. Such a dataset hardly exists, if at all. In reality, most data sets have to be transformed or have data quality issues that need to be dealt with prior to being used for machine learning. This is what the third stage in the machine learning process is all about, data preparation. Data preparation is a process of making sure that our data is suitable for the machine learning approach that we choose to use. Specifically data preparation involves modifying or transforming the structure of our data in order to make it easier to work with. One of the most common ways to transform this structure of data is known as normalization or standardization. The goal of normalization is to ensure that the values of a feature share a particular property, this often involves scaling the data to fall within a small or specified…

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