Learn Data Science: Data Preprocessing in Data Mining & Machine Learning | Part 2

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Data Preprocessing is the most crucial step while solving a problem using Data Science because the real-world data is far from perfect. It can not be used directly within the Machine Learning algorithms. Hence, the data needs to be made more suitable before even beginning to use it.

Data Preprocessing refers to the steps applied to make data more suitable for data mining.

This video is a two-part video and focuses on conceptual components of data preprocessing.

The second part covers the following topics:
00:00 - Introduction
00:40 - Feature Subset Selection
01:35 - Embedded approaches
01:52 - Filter approaches
02:18 - Wrapper approaches
03:06 - Feature Creation
03:52 - Feature extraction
04:42 - Feature Construction
05:20 - Mapping data to new space
06:00 - Discretization & Binarization
08:25 - Variable Transformation
09:54 - Outro

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