AI/ML Interview: Model Evaluation Metrics — Precision, Recall, F1, AUC-ROC, Confusion Matrix, Cross-Validation
Choosing the right evaluation metric is as important as choosing the right model. Using accuracy for an imbalanced fraud detection […]
Choosing the right evaluation metric is as important as choosing the right model. Using accuracy for an imbalanced fraud detection […]
Webhooks are the standard mechanism for event-driven integration between services. Stripe notifies merchants of payments, GitHub notifies CI systems of
Data preprocessing and feature engineering are responsible for 80% of ML project success — not the model architecture. Understanding how
Computer vision is one of the most mature and widely deployed areas of machine learning — powering autonomous vehicles, medical
NLP powers search engines, chatbots, content moderation, machine translation, and document understanding. With the rise of LLMs, NLP has been
Feature flag platforms like LaunchDarkly, Unleash, and Split enable teams to decouple deployment from release, run experiments, and manage risk
Vector databases power semantic search, recommendation systems, and RAG pipelines by storing and querying high-dimensional embedding vectors. Understanding how vector
MLOps (Machine Learning Operations) bridges the gap between training a model in a notebook and running it reliably in production.
Datadog monitors infrastructure and applications for thousands of organizations, ingesting trillions of data points per day across metrics, logs, and
Large Language Models (LLMs) like GPT-4, Claude, and LLaMA have transformed software engineering. Understanding how to deploy, fine-tune, and evaluate
Cloudflare Workers run JavaScript at the edge in 300+ cities worldwide with sub-millisecond cold starts. Designing an edge computing platform
The Transformer architecture (Vaswani et al., 2017, “Attention Is All You Need”) is the foundation of modern AI — powering
Terraform Cloud manages infrastructure-as-code for thousands of organizations, handling state storage, plan/apply workflows, and provider plugin execution. Designing an IaC
Understanding how neural networks learn is fundamental to any ML engineering interview. This guide covers the training process from forward
Ticketmaster sells 500+ million tickets per year with extreme traffic spikes: a popular concert on-sale can attract millions of users