This repository is a comprehensive collection of interview questions and answers for AI/ML roles, focusing on Deep Learning, Large Language Models (LLMs), and Computer Vision. It aims to serve as a valuable resource for job seekers, researchers, and practitioners by covering fundamental concepts, cutting-edge advancements, and practical implementation details.

How It Works

The project is structured into six main thematic modules: LLMs, Computer Vision & Perception Algorithms, Deep Learning Fundamentals & Frameworks, Industry-Specific Domains (Autonomous Driving, Healthcare), Hands-on Coding Projects, and Recommended Open-Source Resources. It continuously updates with the latest interview questions, drawing from high-frequency questions at major tech companies, recent academic papers, and practical industry challenges. The goal is to provide in-depth explanations that stimulate thought and aid in academic research, work innovation, and career advancement.

Quick Start & Requirements

This repository is a curated list of questions and resources, not a runnable software project. No installation or specific requirements are needed to access the information.

Highlighted Details

• Extensive coverage of LLM topics including fine-tuning (LoRA, P-tuning), model architectures (Decoder-only, GPT, LLaMA), and optimization techniques (hallucination reduction, prompt generalization).
• Detailed questions on Computer Vision, covering CNNs, Transformers (ViT, DEIT), diffusion models (Stable Diffusion), object detection (YOLO, FCOS), and segmentation (SAM, U-Net).
• In-depth discussions on Deep Learning fundamentals, PyTorch operations, and training frameworks (TensorRT, MMengine, PyTorch Lightning).
• Specialized sections for Autonomous Driving and Healthcare AI, addressing domain-specific challenges and solutions.
• A dedicated section for coding practice, including implementations of core DL components in PyTorch and NumPy.

Maintenance & Community

The project is actively maintained and encourages community contributions. Links to WeChat official accounts and author's WeChat are provided for joining discussion groups on AI models, open-source projects, and interview experiences.

Licensing & Compatibility

The repository itself is a collection of information and does not have a specific software license. The content is intended for educational and informational purposes.

Limitations & Caveats

Some questions may not yet have complete answers or detailed explanations, with plans to address these gaps. The current organization of questions lacks explicit dimensions for frequency, difficulty, or detailed categorization, though future improvements are planned.