Here are the top ML Fundamentals interview questions to prepare for your next role. Targeting a specific company? Read 20 Google AI/ML interview questions — five of them are playable directly in the article.
1️⃣ What is semi-supervised learning?
- A) A machine learning approach where all data is labeled.
- B) A machine learning approach where no data is labeled.
- C) A machine learning approach where both labeled and unlabeled data are used.
- D) A machine learning approach where data is labeled by clustering algorithms.
2️⃣ Define F1-score
- A) The harmonic mean of precision and recall
- B) The average of precision and recall
- C) Precision multiplied by recall
- D) The square root of precision divided by recall
3️⃣ What's the trade-off between bias and variance?
- A) High bias leads to underfitting, while high variance leads to overfitting.
- B) High bias and high variance both lead to overfitting.
- C) High bias leads to overfitting, while high variance leads to underfitting.
- D) Bias and variance have no impact on the model's performance.
4️⃣ What are common techniques to handle missing data?
- A) Imputation by Mean/Median/Mode
- B) Removing Rows with Missing Values
- C) Adding Random Noise to Missing Values
- D) Model-Based Imputation
5️⃣ How do you combat the curse of dimensionality?
- A) Use Principal Component Analysis (PCA)
- B) Increase the number of features
- C) Reduce the size of the dataset
- D) Use more complex models