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ai

通用

• Microsoft: AI-For-Beginners
  • I Introduction to AI
  • II Symbolic AI
  • III Introduction to Neural Networks
  • IV Computer Vision
  • V. NLP
  • VI. Other
  • VII. Ethics
• Microsoft: Machine Learning for Beginners
  • 1. Introduction
  • 2. Regression
  • 3. Web-App
  • 4. Classification
  • 5. Clustering
  • 6. NLP
  • 7. TimeSeries
  • 8. Reinforcement
  • 9. Real-World
• Microsoft: Generative AI For Beginners
  • 第一章: 简介
  • 第二章: 不同的 LLMs对比
  • 第三章: AI安全
  • 第四章: 提示工程基础
  • 第五章: 提示工程进阶
  • 第八章: 创建搜索应用
• Getting Started with OpenCV
• Microsoft Learn: Introduction to PyTorch
  • 简介
• Microsoft Learn: Introduction to NLP with PyTorch
  • 简介
  • 2. Representing text as Tensors
  • 3. Bag-of-Words and TF-IDF representations
  • 4. Embeddings
• HuggingFace: Learn
• Kaggle Learn
  • Intermediate Machine Learning
  • Intro to Deep Learning
  • 参考
• scikit-learn 1.3.2

2024年

• Build a Large Language Model (From Scratch)
  • 1. Understanding LLM
  • 2. Working with Text Data
  • 3. Coding Attention Mechanisms
  • 4 Implementing a GPT model from Scratch To Generate Text
  • 5 Pretraining on Unlabeled Data
  • 6 Fine-tuning for classification
  • 7 Fine-tuning to follow instructions
  • Appendix A. Introduction to PyTorch
  • Appendix B. References and Further Reading
  • Appendix C. Exercise Solutions
  • Appendix D. Adding Bells and Whistles to the Training Loop
  • appendix E Parameter-efficient fine- tuning with LoRA
  • 其他
• 动手学深度学习(Dive into Deep Learning)
  • 前言
  • Part 1: Basics and Preliminaries
  • Part 2: Modern Deep Learning Techniques
  • Part 3: Scalability, Efficiency, and Applications

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