What is machine learning? |
Difference between AI, ML, and Deep Learning? |
What is supervised learning? |
What is unsupervised learning? |
What is semi-supervised learning? |
What is reinforcement learning? |
What is the difference between inductive and deductive learning? |
What is the difference between training and testing data? |
What is generalization in ML? |
What is a hypothesis in machine learning? |
What is data normalization? |
What is data standardization? |
Why do we need feature scaling? |
How do you handle missing values? |
What are outliers and how to treat them? |
What is the use of data augmentation? |
What is the difference between label encoding and one-hot encoding? |
How to handle imbalanced datasets? |
What is SMOTE? |
What is the impact of noisy data on ML? |
What is feature extraction? |
What is feature selection? |
What is recursive feature elimination? |
What is dimensionality reduction? |
Explain mutual information. |
Explain PCA and its use. |
What is multicollinearity? |
How does correlation affect features? |
What is variance threshold? |
What is feature importance? |
Explain linear regression. |
What are assumptions of linear regression? |
What is logistic regression? |
What is the cost function in linear regression? |
What is the sigmoid function? |
Difference between linear and logistic regression? |
What is decision tree? |
How does pruning help in decision trees? |
What is entropy and information gain? |
Explain support vector machines. |
What is clustering? |
Explain k-means clustering. |
How to select k in k-means? |
What is the elbow method? |
What is hierarchical clustering? |
What is DBSCAN? |
What is dimensionality reduction? |
What is t-SNE? |
What is ICA? |
What is latent semantic analysis? |
What is bagging? |
What is boosting? |
What is the difference between bagging and boosting? |
Explain random forest. |
What is out-of-bag error? |
Explain AdaBoost. |
Explain XGBoost. |
What is LightGBM? |
What is CatBoost? |
Why do ensembles often perform better? |
What is accuracy? |
What is precision? |
What is recall? |
What is F1-score? |
What is specificity? |
What is ROC curve? |
What is AUC score? |
What is log loss? |
What is a confusion matrix? |
What are Type I and II errors? |
What is gradient descent? |
Difference between batch and stochastic gradient descent? |
What is mini-batch gradient descent? |
What is learning rate? |
What are the types of cost/loss functions? |
What is momentum in gradient descent? |
What is Nesterov accelerated gradient? |
What is Adam optimizer? |
What is RMSProp? |
What is weight initialization? |
What is overfitting? |
What is underfitting? |
What is L1 regularization? |
What is L2 regularization? |
What is dropout? |
What is early stopping? |
What is ridge regression? |
What is lasso regression? |
What is elastic net? |
How do you identify overfitting? |
What is Bayes Theorem? |
What is a Gaussian distribution? |
What is p-value? |
What is the Central Limit Theorem? |
What is variance and standard deviation? |
What is skewness? |
What is kurtosis? |
What is a confidence interval? |
What is correlation vs. causation? |
What is hypothesis testing? |
What is deep learning? |
What is a neural network? |
What is a perceptron? |
What is a hidden layer? |
What is backpropagation? |
What is an activation function? |
Explain ReLU. |
What is softmax? |
What is a convolutional neural network? |
What is a pooling layer? |
What is an RNN? |
What is LSTM? |
What is GRU? |
What is attention mechanism? |
What is a transformer? |
What is self-attention? |
What is a GAN? |
What is encoder-decoder architecture? |
What is fine-tuning? |
What is transfer learning? |
What is NLP? |
What is tokenization? |
What is stemming? |
What is lemmatization? |
What is stop-word removal? |
What is TF-IDF? |
What is n-gram? |
What are word embeddings? |
What is Word2Vec? |
What is BERT? |
How do you deploy an ML model? |
What is a REST API? |
What is containerization? |
What is Docker? |
What is Flask? |
What is model serialization? |
What is pickle in Python? |
What is ONNX? |
How to monitor deployed models? |
What is concept drift? |
What is TensorFlow? |
What is Keras? |
What is PyTorch? |
What is Scikit-learn? |
What is Pandas? |
What is NumPy? |
What is Dask? |
What is MLflow? |
What is Weights & Biases? |
What is Hugging Face Transformers? |
What is a time series? |
What is stationarity? |
What is autocorrelation? |
What is ARIMA? |
What is seasonality? |
What is ACF and PACF? |
How do you forecast future values? |
What is Prophet? |
What are lag features? |
How to evaluate time series models? |
How would you detect spam emails? |
How would you detect fraud transactions? |
How would you build a recommendation system? |
How would you classify customer sentiment? |
How would you build a price prediction model? |
How do you approach a churn prediction problem? |
How would you build a credit scoring model? |
How would you build a fake news detector? |
How would you build a resume parser? |
How do you do demand forecasting? |
What is MLOps? |
What is CI/CD in ML? |
What is feature store? |
What is model registry? |
What is experiment tracking? |
What is model governance? |
What is SageMaker? |
What is Azure ML? |
What is Google AI Platform? |
How do you scale ML models in production? |
What is model bias? |
What is fairness in ML? |
What is explainability? |
What is model interpretability? |
What is SHAP? |
What is LIME? |
What are ethical concerns in ML? |
What is differential privacy? |
What is federated learning? |
How to handle sensitive features? |
How do you choose an algorithm? |
How do you debug a poor model? |
How do you deal with multicollinearity? |
When to use deep learning over traditional ML? |
How do you detect data leakage? |
What is the role of cross-validation? |
How do you detect outliers? |
What is A/B testing? |
What is a null hypothesis? |
How do you do hyperparameter tuning? |
Design a real-time recommendation system. |
Design a model to detect anomalies in time series. |
Design a spam detection system. |
Design a ranking model for search engines. |
Design a system for face recognition. |
What is the difference between supervised and unsupervised learning? |
What is overfitting and underfitting? |
What are bias and variance in ML? |
What is the bias-variance trade-off? |
What is cross-validation? |
What is the difference between classification and regression? |
What is a confusion matrix? |
What is precision, recall, and F1-score? |
What is the curse of dimensionality? |
What is the difference between parametric and non-parametric models? |
Explain how Decision Trees work. |
What is the difference between bagging and boosting? |
What is Random Forest and how does it work? |
How does the k-NN algorithm work? |
How does the Naive Bayes classifier work? |
Explain how Support Vector Machines (SVM) work. |
How does gradient descent work? |
What is logistic regression? |
Explain K-means clustering. |
What is PCA and why is it used? |
What is ROC curve? |
How do you interpret AUC-ROC? |
What is the difference between L1 and L2 regularization? |
What is the role of a validation set? |
What is an R² score in regression? |
How do you detect model drift? |
What are Type I and Type II errors? |
What is the difference between Gini Impurity and Entropy? |
What is the ELBO in variational inference? |
How does XGBoost work? |
What is the vanishing gradient problem? |
What is transfer learning? |
What is a generative adversarial network (GAN)? |
What is attention in neural networks? |
How does a transformer model work? |
What is the role of the softmax function? |
What is BERT? |
What techniques can be used for feature selection? |
How do you handle missing data? |
How would you deal with categorical variables? |
What is one-hot encoding? |
What is feature scaling? |
Difference between normalization and standardization? |
What is tokenization? |
What is stemming vs. lemmatization? |
What is TF-IDF? |
What are word embeddings? |
What is the difference between BOW and Word2Vec? |
How does LSTM work? |
What is the role of attention in NLP? |
How do you deploy a machine learning model? |
What is model versioning? |
What is a pipeline in ML? |
What is model monitoring? |
What is A/B testing in machine learning? |
Difference between TensorFlow and PyTorch? |
What is Scikit-learn used for? |
What are the advantages of using MLflow? |
What is the use of DVC? |
What are some tools used for hyperparameter tuning? |
How would you detect fraud in transactions? |
How would you build a recommendation system? |
How would you handle an imbalanced dataset? |
How do you select the right evaluation metric? |
How do you improve a model?s performance? |