Saba Khalil
Take this short quiz to check your understanding of core ML concepts.
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Question of
What is the best definition of Machine Learning?
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A) The process of computers automatically executing a pre-defined set of instructions.
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B) A field of study that gives computers the ability to learn and improve from experience without being explicitly programmed.
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C) The practice of manually analyzing large datasets to find patterns.
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D) A type of programming exclusively used for building websites.
Correct Wrong
A field of study that gives computers the ability to learn and improve from experience without being explicitly programmed. This is the core definition coined by Arthur Samuel.
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Question of
Which of the following is a common example of a Supervised Learning task?
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A) Grouping customers into different segments based on their purchase history.
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B) Reducing a dataset of 100 features down to 3 key features for visualization.
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C) Training a model to predict house prices based on features like size and location.
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D) An AI playing a game against itself to improve its strategy.
Correct Wrong
Training a model to predict house prices based on features like size and location. This is a classic regression problem (a type of supervised learning) where the model learns from labeled data (houses with known prices)
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Question of
What is the term for a model that performs well on the training data but poorly on new, unseen data?
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A) Underfitting
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B) Overfitting
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C) Generalization
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D) Cross-validation
Correct Wrong
Overfitting. This occurs when a model learns the training data too well, including its noise and random fluctuations, and fails to capture the underlying pattern, leading to poor performance on new data.
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Question of
In a dataset used to predict whether an email is “spam” or “not spam,” the label (spam/not spam) is known. What type of learning is this?
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A) Unsupervised Learning
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B) Supervised Learning
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C) Reinforcement Learning
Correct Wrong
Supervised Learning. Since the model is trained on emails with known labels ("spam" or "not spam"), it is a supervised learning task.
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Question of
The task of predicting a category (like “cat” or “dog”) is known as:
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A) Regression
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B) Clustering
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C) Classification
Correct Wrong
Classification tasks predict discrete categories or classes.
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Question of
What is the primary purpose of splitting a dataset into “training” and “testing” sets?
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A) To make the dataset larger.
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B) To ensure the model is trained on all available data.
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C) To evaluate how well the model will perform on new, unseen data.
Correct Wrong
To evaluate how well the model will perform on new, unseen data. The testing set acts as a proxy for real-world data, allowing us to measure the model's ability to generalize.
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