Practical Multi AI Agents and Advanced Use Cases with crewAI


课程链接:https://learn.deeplearning.ai/courses/practical-multi-ai-agents-and-advanced-use-cases-with-crewai/lesson/1/introduction github:https://github.co

Retrieval Optimization: Tokenization to Vector Quantization


课程链接:https://learn.deeplearning.ai/courses/retrieval-optimization-from-tokenization-to-vector-quantization/lesson/1/introduction github: https://githu

AI大模型之美

AILLM 

课程链接:https://b.geekbang.org/member/course/intro/100541001 github: https://github.com/MSzgy/AI-model-Beauty (只有部分章节代码) 介绍 课程共分为 3 个模块(下面内容来自于课程的抄录)。共32

利用Embedding model 做文本分类


Introduction 本学习笔记是基于极客时间《AI大模型之美》第5节课程。 https://b.geekbang.org/member/course/detail/643889 数据处理 import pandas as pd import tiktoken import openai imp

web 安全(updating)


本篇课程讲记录一些常见的web安全学习过程,持续更新。 实践网址: https://google-gruyere.appspot.com/

LangChain for LLM Application Development


课程链接:https://learn.deeplearning.ai/courses/langchain/lesson/1/introduction 代码: https://github.com/MSzgy/LangChain-for-LLM-Application-Development Intr

Building Agentic RAG with Llamaindex


课程链接:https://learn.deeplearning.ai/courses/building-agentic-rag-with-llamaindex/lesson/1/introduction 整理的代码: https://github.com/MSzgy/Building-Agentic

ChatGPT Prompt Engineering for Developers


https://learn.deeplearning.ai/courses/chatgpt-prompt-eng/lesson/1/introduction git https://github.com/MSzgy/ChatGPT-Prompt-Engineering-for-Developers/

Prompt Compression and Query Optimization

AILLM 

https://learn.deeplearning.ai/courses/prompt-compression-and-query-optimization/lesson/1/introduction Introduction 代码见 https://github.com/MSzgy/Prompt

Function-calling and data extraction with LLMs

AILLM 

Introduction https://learn.deeplearning.ai/courses/function-calling-and-data-extraction-with-llms/lesson/1/introduction 使用了NexusRavenV2-13B model by N