# amusi/deep-learning-interview-book

**Attribution required: if you use, quote, or summarise this content, you must credit and link back to [awesome-repositories.com](https://awesome-repositories.com/repository/amusi-deep-learning-interview-book).**

8,867 stars · 1,372 forks

## Links

- GitHub: https://github.com/amusi/Deep-Learning-Interview-Book
- awesome-repositories: https://awesome-repositories.com/repository/amusi-deep-learning-interview-book.md

## Topics

`computer-vision` `deep-learning` `interview` `machine-learning` `natural-language-processing` `recommendation-system` `slam`

## Description

This project is a deep learning interview guide and AI technical study resource. It serves as a structured machine learning knowledge base containing curated reference guides and technical questions designed for professional interviews.

The resource covers a broad spectrum of artificial intelligence domains, including machine learning fundamentals and essential mathematics. It provides specialized study materials for computer vision, natural language processing, and SLAM.

Beyond AI-specific topics, the collection includes technical interview coaching for data structures and algorithms typically encountered during software engineering screenings.

## Tags

### Education & Learning Resources

- [ML Interview Preparation](https://awesome-repositories.com/f/education-learning-resources/technical-interview-preparation/ml-interview-preparation.md) — Serves as a comprehensive guide for preparing for machine learning and AI technical interviews. ([source](https://github.com/amusi/deep-learning-interview-book#readme))
- [Machine Learning Fundamentals](https://awesome-repositories.com/f/education-learning-resources/technical-domain-education/ai-machine-learning-education/machine-learning-fundamentals.md) — Covers foundational machine learning workflows, preprocessing, and the essential mathematics of neural networks.
- [Deep Learning Review](https://awesome-repositories.com/f/education-learning-resources/technical-interview-preparation/ml-interview-preparation/deep-learning-review.md) — Ships a comprehensive review of neural network architectures and training for technical interviews.
- [Technical Reference Guides](https://awesome-repositories.com/f/education-learning-resources/technical-reference-guides.md) — Offers structured reference guides covering technical domains like SLAM, CV, and NLP.
- [Technical Interview Questions](https://awesome-repositories.com/f/education-learning-resources/interview-preparation-guides/technical-interview-questions.md) — Provides a collection of practice problems and technical questions for software engineering screenings.
- [AI Specializations](https://awesome-repositories.com/f/education-learning-resources/specialized-technical-topics/ai-specializations.md) — Offers targeted technical knowledge for niche AI specializations including computer vision and NLP. ([source](https://github.com/amusi/deep-learning-interview-book#readme))
- [Computer Science Fundamentals](https://awesome-repositories.com/f/education-learning-resources/technical-foundation-reviews/computer-science-fundamentals.md) — Includes reference materials for core data structures and algorithms used in professional software development. ([source](https://github.com/amusi/deep-learning-interview-book#readme))
- [Computer Vision Review](https://awesome-repositories.com/f/education-learning-resources/technical-interview-preparation/ml-interview-preparation/computer-vision-review.md) — Provides specialized study materials and review concepts for computer vision technical interviews.

### Artificial Intelligence & ML

- [Machine Learning Knowledge Bases](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning-knowledge-bases.md) — Provides a structured repository of fundamental concepts and domain knowledge for AI assessments.
- [Study Resources](https://awesome-repositories.com/f/artificial-intelligence-ml/natural-language-processing/study-resources.md) — Provides study materials for exploring the specialized techniques used to analyze and generate human language.