This repository curates a comprehensive learning path for AI, targeting aspiring engineers and researchers. It provides a structured roadmap for acquiring foundational knowledge in Python, deep learning frameworks like PyTorch, and core machine learning concepts, with a focus on practical application through video tutorials, notes, and project suggestions.

How It Works

The learning path is organized into distinct modules, starting with Python fundamentals and progressing to deep learning and machine learning. It leverages a mix of popular online video courses (Bilibili, Coursera) and curated GitHub repositories for notes and code. The approach emphasizes learning through both theoretical understanding and hands-on practice with recommended projects and foundational models like RNNs, LSTMs, and BERT.

Quick Start & Requirements

• Installation: No specific installation commands are provided as this is a curated list of resources.
• Prerequisites: Access to the internet for video streaming and GitHub repositories. Familiarity with basic programming concepts is beneficial.
• Resources: Requires a computer with internet access. Video courses may have varying bandwidth requirements.
• Links:
  • Python: 莫烦python, 小甲鱼python, 慕课网python3
  • PyTorch: 刘二大人, 七月在线-褚则伟, 李沐
  • Deep Learning: 李沐《动手学深度学习v2》, MLNLP-World/DeepLearning-MuLi-Notes, 吴恩达 deep_learning_ai, fengdu78/Coursera-ML-AndrewNg-Notes
  • Machine Learning: 吴恩达机器学习, 李宏毅机器学习
  • NLP: cs224n
  • CV: cs231n

Highlighted Details

• Comprehensive coverage from Python basics to advanced NLP and CV topics.
• Integrates multiple learning styles with video lectures, written notes, and code examples.
• Recommends specific projects for practical skill development in NLP and CV.
• Includes essential tools for research such as LaTeX, Markdown, Linux, and Anaconda.

Maintenance & Community

• The repository appears to be a personal curation, with no explicit mention of maintainers, community channels, or a roadmap. Updates are implied through the "Follow关注仓库的更新☺..." note.

Licensing & Compatibility

• The repository itself does not contain code that would typically require licensing. It links to external resources, whose licenses would apply individually. Compatibility for commercial use depends on the licenses of the linked external materials.

Limitations & Caveats

This repository is a curated list of external resources and does not provide original code or direct learning environments. The quality and availability of linked materials are subject to external factors. The learning path is a personal recommendation and may not suit all learning styles or cover all niche AI topics.