Topics asked at interviews for ML practitioners in Germany

𝗠𝗟 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀

• Variance-Bias Trade-off

• Regression Algorithms

• Classification Algorithms

• Clustering Algorithms

• Deep Learning (DNN, LSTM, Transformers)

• Regularization Methods

• Model Evaluation Metrics

• Handling Missing Data

• Feature Scaling

• Dimensionality Reduction

• Encoding Categorical Data

• Hyperparameter Tuning

• Cross-validation

𝗠𝗟 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻

• Chatbot

• RAG

• Recommenders

• Fraud detection

• Image classification

• Voice recognition

(usually you asked design questions for a system you will work on, e.g if you apply to a team building chatbot, you will ask how to design a chatbot)

𝗠𝗟 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁

• Model Serving (Batch vs Real-Time)

• Monitoring and Maintaining Models in Production

• Model Retraining Strategies

• Workflow Orchestration

• Experiment Tracking 

• Model Registry and Versioning