| 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? |
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