Discover the key principles of machine learning and how to effectively demonstrate them, as explained by an expert in the IBM Artificial Intelligence Fundamentals certification. Ace your exam with this comprehensive guide.
Table of Contents
Question
How can you demonstrate the concept of machine learning?
A. Determine how hot a cup of coffee should be by consulting a list of preferred brewing temperatures.
B. Determine the best way to book airline connections by running through a decision tree of possible flights, destinations, and departure dates and times.
C. Every day for two weeks, ask a librarian what books to read and keep a record of each recommendation.
D. Determine the farthest distance from a target that an archer can reliably hit bullseyes by shooting arrows repeatedly while walking closer and closer to the target.
Answer
D. Determine the farthest distance from a target that an archer can reliably hit bullseyes by shooting arrows repeatedly while walking closer and closer to the target.
Explanation
Shooting arrows at a target from gradually shorter distances could describe machine learning’s way of performing a series of calculations (similar to shooting arrow at different distances) and noting correlated results in order to increase the accuracy of its algorithms.
Machine learning is the process of training a computer system to learn from data, without being explicitly programmed. In the context of this question, option D best demonstrates the concept of machine learning.
By repeatedly shooting arrows at a target and walking closer to it, the archer is collecting data on the distance at which they can reliably hit the bullseye. This data can then be used to train a machine learning model that can predict the farthest distance at which the archer can consistently hit the target.
The key aspects of machine learning demonstrated in this scenario are:
- Data collection: The archer is gathering data by repeatedly shooting arrows and recording the results.
- Model training: The collected data can be used to train a machine learning model that can predict the optimal distance for the archer.
- Iterative improvement: As the archer collects more data by moving closer to the target, the machine learning model can be refined and improved to make more accurate predictions.
In contrast, the other options do not demonstrate the core principles of machine learning. Option A involves consulting a pre-determined list of preferred brewing temperatures, which is a rule-based approach rather than a machine learning one. Option B involves running through a decision tree, which is a form of rule-based decision-making, not machine learning. Option C involves asking a librarian for recommendations, which is a manual process and does not involve any machine learning.
Therefore, option D is the correct answer as it best showcases the key concepts of machine learning, such as data collection, model training, and iterative improvement.
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