- A
Learning rate
Learning rate controls the step size during optimization and is crucial for convergence.
- B
Batch size
Why wrong: Batch size can affect training speed and stability, but for BlazingText it's less critical than learning rate and epochs.
- C
Loss function
Why wrong: BlazingText uses a fixed loss function (softmax or negative sampling) and does not allow changing it.
- D
Type of optimizer
Why wrong: BlazingText uses a fixed optimizer (SGD with negative sampling) and does not allow changing it.
- E
Number of epochs
Number of epochs determines how many times the model sees the training data, affecting under/overfitting.
Quick Answer
The answer is number of epochs and learning rate, as these two hyperparameters are most important to tune for improving model accuracy with BlazingText. When training a neural network like BlazingText for text classification, the learning rate controls the step size during gradient descent, determining how quickly the model converges toward a minimum loss, while the number of epochs defines how many complete passes the algorithm makes over the entire training dataset. Tuning these together prevents underfitting from too few epochs or overshooting the optimum from an excessively high learning rate. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding that BlazingText, despite being a built-in algorithm, still requires careful hyperparameter optimization—a common trap is focusing on batch size or negative sampling instead. Remember the memory tip: "Epochs and rate determine your model's fate."
MLS-C01 Modeling Practice Question
This MLS-C01 practice question tests your understanding of modeling. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data scientist is training a text classification model using Amazon SageMaker's built-in BlazingText algorithm. The dataset contains 1 million documents. Which TWO hyperparameters are most important to tune for improving model accuracy?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Learning rate
Learning rate and number of epochs are critical hyperparameters for training neural networks like BlazingText. They control how quickly the model learns and how long it trains.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Learning rate
Why this is correct
Learning rate controls the step size during optimization and is crucial for convergence.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Batch size
Why it's wrong here
Batch size can affect training speed and stability, but for BlazingText it's less critical than learning rate and epochs.
- ✗
Loss function
Why it's wrong here
BlazingText uses a fixed loss function (softmax or negative sampling) and does not allow changing it.
- ✗
Type of optimizer
Why it's wrong here
BlazingText uses a fixed optimizer (SGD with negative sampling) and does not allow changing it.
- ✓
Number of epochs
Why this is correct
Number of epochs determines how many times the model sees the training data, affecting under/overfitting.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Learning rate — Learning rate and number of epochs are critical hyperparameters for training neural networks like BlazingText. They control how quickly the model learns and how long it trains.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
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