Machine Learning: Random Forest with Python from Scratch - Importing Data, Helper Functions

The video tutorial covers importing a dataset using pandas, preparing it by converting it into a list, and shuffling it to ensure randomness. It then explains how to split the data into training and testing sets. The tutorial also introduces three helper functions: one to find unique values, another to count class occurrences, and a third to check if a value is numeric. These functions are essential for later stages of data analysis and machine learning tasks.

How do you split a dataset into training and testing sets?

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What are helper functions and why are they important in coding?

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Explain the purpose of the 'unique values' function.

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What does the 'class count' function do in the context of machine learning?

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