Concept Interview Questions

Review this list of 203 Concept interview questions and answers verified by hiring managers and candidates.

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Define the scope and requirements for a snake_case to camelCase converter function.
6 months ago
How do you troubleshoot the log events in Splunk's admin UI?
2 years ago
What is the purpose of a Weibull distribution?
5 years ago
Explain how you handle data scarcity.
3 years ago
Explain cross-validation and testing in logistic regression.
3 years ago
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What is caching and why is it needed?
5 years ago1 answer
Which is more likely to result in overfitting a model? More training data, decreased nodes in neural network hidden layers, eliminating sparse features, or using a Gaussian or RBF kernel in SVM?
1 answer
You're a PM at Fivetran. Prepare a presentation explaining one of Fivetran's connectors.
3 years ago
Explain how you choose a model or algorithm to solve a problem.
3 years ago
What is a fork, process, thread?
2 years ago
What is the Simpson paradox?
2 years ago
What are the testing methodologies for wireless technology?
2 years ago
What are the best practices for data visualization?
2 years ago
What's the difference between layer 1 and layer 2 blockchain?
2 years ago
Explain the differences between LSTM and traditional neural networks.
3 years ago
What is the significance of an area under the curve (AUC) equal to 0.5?
1 answer
Explain cross entropy.
3 years ago
Where do vanishing gradients occur in a neural network?
3 years ago
Explain linear regression to a non-technical stakeholder.
Explain regularization.
3 years ago

Showing 141-160 of 203

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Concept Interview Questions

Define the scope and requirements for a snake_case to camelCase converter function.

How do you troubleshoot the log events in Splunk's admin UI?

What is the purpose of a Weibull distribution?

Explain how you handle data scarcity.

Explain cross-validation and testing in logistic regression.

What is caching and why is it needed?

Which is more likely to result in overfitting a model? More training data, decreased nodes in neural network hidden layers, eliminating sparse features, or using a Gaussian or RBF kernel in SVM?

You're a PM at Fivetran. Prepare a presentation explaining one of Fivetran's connectors.

Explain how you choose a model or algorithm to solve a problem.

What is a fork, process, thread?

What is the Simpson paradox?

What are the testing methodologies for wireless technology?

What are the best practices for data visualization?

What's the difference between layer 1 and layer 2 blockchain?

Explain the differences between LSTM and traditional neural networks.

What is the significance of an area under the curve (AUC) equal to 0.5?

Explain cross entropy.

Where do vanishing gradients occur in a neural network?

Explain linear regression to a non-technical stakeholder.

Explain regularization.

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