Machine Learning Interviews

Machine Learning Interviews is an open-source repository that provides a comprehensive collection of resources, guides, and study materials for preparing for machine learning, data science, and AI-related job interviews. The project covers everything from fundamental concepts to advanced system design, helping candidates prepare for interviews at major tech companies like Google, Meta, Amazon, and other leading organizations.

• Comprehensive Study Guide - Covers machine learning fundamentals, deep learning, statistics, probability, and coding challenges with structured learning paths for different experience levels.

• ML System Design Resources - Includes detailed templates and examples for machine learning system design interviews, covering topics like recommendation systems, search ranking, and fraud detection.

• Interview Question Collections - Provides curated lists of commonly asked interview questions across different ML domains including NLP, computer vision, and reinforcement learning.

• Behavioral Interview Preparation - Offers guidance on behavioral questions and soft skills assessment commonly encountered in ML engineering interviews.

• Company-Specific Insights - Contains information about interview processes at various tech companies, helping candidates understand what to expect.

• Coding Practice Resources - Links to relevant coding challenges and practice problems specifically tailored for ML engineering roles.

To get started, clone the repository and navigate through the organized folder structure covering different interview topics. The materials are designed for self-paced study, allowing candidates to focus on areas where they need the most improvement. The repository is regularly updated with new content and community contributions.