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ML/AI Interview Prep
A collection of machine learning and AI interview questions with code and cheat sheets for common data science libraries.
About ML/AI Interview Prep
ML/AI Interview Prep is a GitHub repository that collects machine learning and AI interview questions with code examples and cheat sheets for common data science libraries.
Content is grouped by topic, including ML fundamentals, math and statistics, deep learning, NLP, computer vision, ML system design, Python libraries, coding patterns, and behavioral preparation. Examples include Python code using scikit-learn, PyTorch, and related libraries.
Key features
- ML fundamentals Q&A on bias-variance, overfitting, regularization, loss functions
- Deep learning Q&A on CNNs, RNNs, transformers, attention, training tricks
- NLP Q&A covering BERT, GPT, RAG, embeddings, and tokenization
- Computer vision notes on YOLO, ResNet, augmentation, and segmentation
- ML system design examples for recommendation, search, fraud detection
- Code snippets for NumPy, Pandas, scikit-learn, and PyTorch
Best for: Job seekers preparing for machine learning or AI interviews that involve Python coding and system design.
Good for
- Organizes questions across fundamentals, deep learning, NLP, vision, and system design
- Pairs explanations with Python code using scikit-learn and PyTorch
- Includes system design examples and behavioral material alongside technical Q&A
ML/AI Interview Prep at a glance
- Category
- Education & Learning › Exam Prep
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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