Instead of loading the entire 10GB dataset into a single NumPy array and then passing it around, you can create a generator to process the data in a stream. A generator is a special type of Python function that returns an iterator, which yields items one by one instead of all at once. This allows you to process the data as it's read from the file, effectively keeping only one slice of it in memory at any given time.