Accenture – Machine Learning Interview Questions
Here is the list Machine Learning Interview Questions which are recently asked in Accenture company. These questions are included for both Freshers and Experienced professionals.
- What’s the trade-off between bias and variance?
- What is the difference between supervised and unsupervised machine learning?
- How is KNN different from k-means clustering?
- Explain how a ROC curve works.
- What is Bayes’ Theorem? How is it useful in a machine learning context?
- Why is “Naive” Bayes naive?
- Explain the difference between L1 and L2 regularization
- What’s your favorite algorithm, and can you explain it to me in less than a minute?
- What’s the difference between Type I and Type II error?
- What’s the difference between probability and likelihood?
- What is deep learning, and how does it contrast with other machine learning algorithms?
- What cross-validation technique would you use on a time series dataset?
- How is a decision tree pruned?
- Which is more important to you– model accuracy, or model performance?
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