Preparing for a Machine Learning Interview?

Don’t Miss These Concepts and Questions ↓

1️⃣ Bias-Variance Tradeoff

↳ What is the bias-variance tradeoff?

↳ How do you explain the balance between underfitting and overfitting?

2️⃣ Gradient Descent Algorithm

↳ What is gradient descent?

↳ How does it optimize model parameters?

3️⃣ Dimensionality Reduction & PCA

↳ What does dimensionality reduction mean?

↳ How does PCA achieve it?

4️⃣ Bagging & Random Forests

↳ How does bagging work?

↳ How do Random Forests use it for better predictions?

5️⃣ Regularization & Dropout

↳ How does regularization prevent overfitting?

↳ How does dropout work in neural networks?

6️⃣ Activation Functions

↳ What are activation functions?

↳ Why are they important in neural networks?

7️⃣ Z-scores & Outlier Detection

↳ What is a Z-score?

↳ How can it be used to detect outliers?

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