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A Systematic Approach to Artificial Intelligence Research & Engineering
AI-Practices 是一个系统化、工程化的人工智能学习与研究平台，采用 渐进式学习框架 (Progressive Learning Framework, PLF) 方法论，构建从经典机器学习到前沿深度学习的完整知识体系。
| Metric | Value | Description |
|---|---|---|
| Notebooks | 113+ | 可复现的 Jupyter 实验 |
| Modules | 9 | 核心学习模块 |
| Projects | 19 | 端到端实战项目 |
| Code | 149k+ | 行高质量代码 (PEP8) |
| Kaggle | Gold | 竞赛金牌方案 |
# Clone repository
git clone https://github.com/zimingttkx/AI-Practices.git
cd AI-Practices
# Create Conda environment
conda create -n ai-practices python=3.10 -y
conda activate ai-practices
# Install dependencies
pip install -r requirements.txtpython -c "import tensorflow as tf; print(f'TensorFlow: {tf.__version__}')"
python -c "import torch; print(f'PyTorch: {torch.__version__}')"jupyter lab- Module: Module 01: Foundations
- Focus: 数学推导 + 算法分析
- Output: 理论笔记
- Modules: Module 02: Neural Networks, Module 03: Computer Vision, Module 04: Sequence Models
- Focus: NumPy 从零实现
- Output: 核心代码
- Modules: Module 05: Advanced Topics, Module 06: Generative Models, Module 07: Reinforcement Learning
- Focus: TensorFlow/PyTorch 工程实现
- Output: 生产级代码
- Module: Module 09: Projects
- Focus: 真实项目 + Kaggle 竞赛
- Output: 完整解决方案
- Getting Started - 快速入门指南
- Installation - 详细安装说明
- Quick Start Examples - 快速示例
- Architecture - 系统架构设计
- Methodology - 渐进式学习方法论
- Best Practices - 最佳实践指南
- Module 01: Foundations - 机器学习基础
- Module 02: Neural Networks - 神经网络与深度学习
- Module 03: Computer Vision - 计算机视觉
- Module 04: Sequence Models - 序列模型与 NLP
- Module 05: Advanced Topics - 高级专题
- Module 06: Generative Models - 生成式模型
- Module 07: Reinforcement Learning - 强化学习
- Module 08: Theory Notes - 理论笔记
- Module 09: Projects - 实战项目
- API Reference - API 参考文档
- FAQ - 常见问题解答
- Troubleshooting - 故障排除指南
- Changelog - 版本更新日志
- References - 参考文献
- Contributing - 贡献指南
- Code of Conduct - 行为准则
- TensorFlow 2.13+
- Keras 3.x
- PyTorch 2.x
- Hugging Face Transformers 4.30+
- Scikit-learn 1.3+
- XGBoost 2.0+
- LightGBM 4.0+
- CatBoost 1.2+
- NumPy 1.24+
- Pandas 2.0+
- SciPy 1.10+
- Matplotlib 3.7+
- Seaborn 0.12+
- Python 3.10+
- Jupyter Lab 4+
- Git 2.40+
- Docker 24+
- GitHub Issues: Report bugs
- Documentation: Online Docs
- Discussions: GitHub Discussions
This project is licensed under the MIT License - see the LICENSE file for details.
