ML System Design: Build a Spam Classifier
4 min read “Design a spam classifier” is one of the most common ML system design questions at Google, Meta, and Microsoft. Unlike […] Read article
AI/ML Interview Questions
AI/ML Interview Questions
How Does RLHF Work? Reinforcement Learning from Human Feedback Explained
5 min read RLHF (Reinforcement Learning from Human Feedback) is the technique that transforms a raw language model into an assistant — the Read article
AI/ML Interview Questions
Computer Vision Interview Questions: CNNs, Object Detection, and Transfer Learning
6 min read Computer vision is one of the most interview-tested areas of ML, especially at companies with physical products, autonomous systems, or Read article
AI/ML Interview Questions
What is RAG? Retrieval-Augmented Generation vs Fine-tuning
5 min read Retrieval-Augmented Generation (RAG) is one of the most widely deployed LLM patterns in production. Understanding when to use RAG versus Read article
AI/ML Interview Questions
Embeddings and Vector Databases Explained
6 min read Embeddings are the lingua franca of modern AI applications. They power semantic search, RAG, recommendation systems, duplicate detection, and anomaly Read article
AI/ML Interview Questions
How Transformer Models Work: Attention Mechanism Explained
6 min read Transformers are the architecture behind GPT, BERT, Claude, and every other major language model. Understanding how they work — especially Read article
AI/ML Interview Questions
Fine-tuning LLMs vs Training from Scratch: When and How
6 min read One of the most common LLM interview questions in 2026: “Would you fine-tune a model or train from scratch?” Almost Read article
AI/ML Interview Questions
How to Choose Between Machine Learning Models
5 min read One of the most common ML interview questions isn’t about a specific algorithm — it’s “how do you decide which Read article
AI/ML Interview Questions
Train/Test/Validation Split: The Right Way and Common Mistakes
6 min read Train/test/validation splits are foundational — and routinely misunderstood. The most common mistake in applied ML is using the test set Read article
AI/ML Interview Questions
Feature Selection and Dimensionality Reduction: PCA, Lasso, and Tree Importance
6 min read Feature selection and dimensionality reduction are how you fight the curse of dimensionality — the phenomenon where models trained on Read article
AI/ML Interview Questions
Handling Imbalanced Datasets in Machine Learning
5 min read Imbalanced datasets — where one class dramatically outnumbers another — are the norm in production ML, not the exception. Fraud Read article
AI/ML Interview Questions
Cross-Validation Strategies: K-Fold, Time Series, and Nested CV
5 min read Cross-validation is how you estimate a model’s generalization performance before deploying it. Getting this wrong — especially data leakage — Read article
AI/ML Interview Questions
Classification Metrics: Precision, Recall, F1, and AUC-ROC
6 min read Classification metrics are one of the most frequently misused concepts in ML interviews. The wrong answer: “I use accuracy.” The Read article