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 randomly shuffling it to ensure unbiased training and testing. It then demonstrates splitting the data into training and testing sets. The tutorial also includes writing helper functions to identify unique values, count class occurrences, and check for numeric values, which will be used in later stages of implementing a decision tree.

What is the purpose of the unique values helper function?

How does the class count function work in the context of the dataset?

What is the significance of the is_num function in the code?

Describe the overall process that was implemented in this lecture.