Credit Karma Machine Learning Engineer interview questions.

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64 Credit Karma Machine Learning Engineer questions
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64 questions for Credit Karma Machine Learning Engineer

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ML Knowledge

2 years ago

How does the gradient boost algorithm function in the context of machine learning?

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2 years ago

ML Knowledge

3 years ago

Explain the significance of precision and recall in the field of artificial intelligence, and how they can help in improving the accuracy of machine learning models. Also, mention some common limitations and challenges related to the use of these metrics in practice.

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3 years ago

Coding

3 years ago

Can you present a script to ascertain the longest palindromic sequence in a string?

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3 years ago

Coding

3 years ago

Can you show a code snippet that inverts a binary tree in a programming language you are familiar with?

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3 years ago

Coding

3 years ago

Can you demonstrate a greedy algorithm to find the most concise subarray that meets a specific target sum?

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3 years ago

Coding

3 years ago

Could you draft a Python code that sets up a hash table?

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3 years ago

StatisticsML Knowledge

3 years ago

Could you lay out the meanings of false positives and false negatives in statistical hypothesis testing, and why they play a crucial role in interpreting the results?

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3 years ago

ML KnowledgeML Case

3 years ago

What are your go-to optimization techniques and how do they essentially operate?

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3 years ago

ML Knowledge

3 years ago

Why is it considered essential to account for error assumptions in linear regression, and what does it imply?

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3 years ago

ML Knowledge

4 years ago

Would you be able to provide me with some instances where overfitting and underfitting are common in real-world situations? What are the implications for model accuracy and performance?

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4 years ago

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^*All interview questions are submitted by recent Credit Karma Machine Learning Engineer candidates, labelled and categorized by Prepfully, and then published after being verified by Machine Learning Engineers at Credit Karma.