🧠 ChatGPT Learning Cheatsheet

10 Python Libraries Every AI Engineer Should Know

1. Hugging Face Transformers
A powerful library for using and fine-tuning pre-trained transformer models for NLP. Learn more: Hugging Face NLP Course

2. Ollama
A framework for running and managing open-source LLMs locally with ease. Learn video: Ollama Course

3. OpenAI Python SDK
The official toolkit for integrating OpenAI models into Python applications. Learn more: The official developer quickstart guide

4. Anthropic SDK
A client library for seamless interaction with Claude and other Anthropic models. Learn more: Anthropic Python SDK

5. LangChain
A framework for building LLM applications with modular and extensible components. Learn more: DeepLearning.AI

6. LlamaIndex
A toolkit for integrating custom data sources with LLMs for better retrieval. Learn more: Building Agentic RAG with LlamaIndex

7. SQLAlchemy
A Python SQL toolkit and ORM for efficient and maintainable database interactions. Learn more: SQLAlchemy Unified Tutorial

8. ChromaDB
An open-source vector database optimized for AI-powered search and retrieval. Learn more: Getting Started - Chroma Docs

9. Weaviate
A cloud-native vector search engine for efficient semantic search at scale. Learn more: 101T Work with: Text data

10. Weights & Biases
A platform for tracking, visualizing, and optimizing ML experiments.
Learn more: Effective MLOps: Model Development

#artificialintelligence

Generative vs. discriminative models in ML

LLM Scientist Roadmap 👆

Must know terms in LLM

Python Libraries for Generative AI

Important Plots in Data Science