Feature Engineering v/s Feature Selection

Feature Engineering and Feature Selection for Beginners and Non-Python and Machine Learning Tutorial

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They say the data is the new oil, but we don’t use the oil directly from its source. It must be processed and cleaned before using it for different purposes.

The same goes for data, we don’t use it directly from its source. It also needs to be elaborate.

This can be a challenge for beginners in machine learning and data science because the data comes from different sources with different data types. Therefore it is not possible to apply the same cleaning and processing method to different types of data.

“Information can be extracted from data just as energy can be extracted from oil.” — Adeola Adesina

You have to learn and apply methods depending on the data you have.

After reading this article, you will know:

• What is Feature Engineering and Feature Selection?
• Several methods for dealing with missing data in your dataset.
• Several methods to handle continuous data.
• Different methods for managing categorical data.