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?

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

Explain the purpose of the 'unique values' function.

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