Learn the difference between data and labels when training an AI model to play Tic Tac Toe. Discover how game state images and move feedback are used in the training process.
Table of Contents
Question
While training an AI to play Tic Tac Toe:
A. The game state images are provided as labels
B. The game state images are provided as data
C. Feedback on a particular move (“good” or “bad”) is provided as data
D. Feedback on a particular move (“good” or “bad”) is provided as labels
Answer
B. The game state images are provided as data
D. Feedback on a particular move (“good” or “bad”) is provided as labels
Explanation
When training an AI model to play Tic Tac Toe, it’s crucial to understand the distinction between data and labels:
Data: The data consists of the input information provided to the AI model during training. In this case, the game state images showing the current positions of X’s and O’s on the Tic Tac Toe board serve as the data. The AI model learns to recognize patterns and make decisions based on these game state images.
Labels: Labels, on the other hand, represent the desired output or the correct answers that the AI model should predict. When training the Tic Tac Toe AI, the feedback on each move, indicating whether it was a “good” or “bad” move, acts as the labels. These labels guide the AI model to learn which moves lead to favorable outcomes and which ones should be avoided.
In summary, the game state images are provided as data (input) to the AI model, while the feedback on each move (“good” or “bad”) is provided as labels (desired output). By learning from the combination of data and labels, the AI model gradually improves its ability to make intelligent moves and play Tic Tac Toe effectively.
Google AI for Anyone certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Google AI for Anyone exam and earn Google AI for Anyone certification.