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Large Language Models Tutorials with Jupyter Notebooks

Welcome to my treasure trove of Jupyter Notebooks! 🚀 These notebooks are the companions to my YouTube tutorials, where I share my passion for all things AI, ML, and data science.

Inside, you'll find:

  • Well-documented code examples 💻
  • Clear explanations 📖
  • Hands-on exercises 💪
  • Additional resources to deepen your knowledge 📚

Whether you're a beginner just starting out or a seasoned pro looking for new ideas, I hope these notebooks inspire you to create amazing things with code. Happy learning!

What you'll find:

Diverse Tutorials: Covering a range of topics, from core concepts like embeddings and vector stores to advanced applications like conversational question-answering.

Interactive Notebooks: Designed for hands-on learning, allowing you to run the code and explore the results within your browser.

Clear Explanations: Each notebook provides detailed explanations of the code and results, helping you understand the underlying concepts.

Community & Support: Feel free to raise questions, share feedback, and contribute to the project through the GitHub discussions or issue tracker.

Getting Started:

Clone the repository: Use git clone https://github.com/atef-ataya/Large-Language-Models-Tutorial.git to download the files.

Install requirements: Open a terminal within the repository and run pip install -r requirements.txt to install necessary libraries.

Launch Jupyter Notebooks: Run jupyter notebook in the terminal to start the Jupyter server.

Explore the notebooks: Navigate to the notebooks directory and open any notebook to begin exploring the tutorials.

Notebooks you can try:

LangChain 101: Learn fundamental concepts like embeddings, vector stores, and retrieval.

Summarization with OpenAI: Explore text summarization using OpenAI models and LangChain pipelines.

Conversational Q&A with Pinecone: Build a conversational question-answering system using Pinecone and LangChain.

...and many more!

Feel free to:

By diving into these LangChain tutorials, you'll gain practical skills and expand your understanding of this powerful NLP library. Let's explore the exciting world of LangChain together!

Additional Information:

LangChain Documentation: https://readthedocs.org/projects/langchain/

OpenAI Documentation: https://platform.openai.com/docs/introduction

Jupyter Notebook: https://jupyter.org/

Project Status: Actively Maintained