Practice Model Evaluation And Training (6.3) - Machine Learning Basics

Practice: Model Evaluation and Training

Lesson 6.3Machine Learning Basics

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10 questions

Flashcard drill
3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define the training set in your own words.
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Think about what the model learns from.
Question 2.
What is the purpose of the validation set?
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Consider how it relates to the training process.
3Question 3.
What is the main purpose of the validation set?
- To train the model
- To test the model
- To fine-tune the model parameters
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Consider its role after training.
4Question 4.
True or False: The test set is used during the training process.
- True
- False
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Think about when we evaluate performance.
Question 5.
Design a small machine learning project. Define your dataset, how you would split it into training, validation, and test sets, and explain why you made these choices.
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Consider how each part of the dataset contributes to the model's learning.
Question 6.
Given a model with an accuracy of 90% but a low precision of 40%, analyze what this implies about the model and suggest improvement strategies.
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Think about what aspects can lead to a high accuracy but poor precision.

6 more questions in this section. Enroll free to practise them all.