Lesson 7: Collections — Lists and Loops

AI is all about data, and data rarely comes as a single number. It comes in collections.

In Python, the most common way to store a collection of items is a List.

Lists: Ordered Collections

A list is created using square brackets []. You can store numbers, strings, or even other lists inside.

predictions = [0.9, 0.1, 0.8, 0.4]
labels = ["cat", "dog", "bird"]

You can access items in a list using their index. Remember, Python is "zero-indexed", meaning the first item is at index 0.

print(labels[0]) # Output: cat

Loops: Automating Repetition

To do something with every item in a list, we use a for loop. This is crucial for iterating through datasets or simulating training steps!

for score in predictions:
print(score)

If you want to loop a specific number of times, you can use the range() function:

for i in range(5):
print(f"Training Epoch {i}")

Coding Challenge: Evaluating Predictions

Let's simulate evaluating a model. You have a list of prediction scores between 0 and 1. We want to count how many predictions are above our threshold.

Create a list scores = [0.9, 0.3, 0.7, 0.85, 0.2, 0.95].
Create a variable high_confidence_count and set it to 0.
Write a for loop to go through each score in scores.
Inside the loop, use an if statement to check if the score is greater than 0.8. If it is, add 1 to your count.
After the loop, print() the final count.