Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Pre-Processing

The video tutorial covers data preprocessing using the sklearn library, focusing on the implementation of the Standard Scaler to scale data features to a specific range. This process helps the algorithm better understand the impact of each attribute, improving model performance. The tutorial demonstrates how to prepare the dataset for classifier input by scaling data values to a range of -2 to 2, ensuring the data is ready for further analysis.

How does scaling help the algorithm understand the attributes better?

What steps were taken to prepare the dataset for the classifier?