ashishpatel26/The-Industrialization-of-NLP-to-Large-Language-Model-Engineering

From Research to Production: The Industrialization of NLP to Large Language Model Engineering

The-Industrialization-of-NLP-to-Large-Language-Model-Engineering

Welcome to the repository for the book "From Research to Production: The Industrialization of NLP to Large Language Model Engineering." This repository contains code and notebooks accompanying the chapters of the book. Please refer to the following sections for more details.

Table of Contents

1. Part 1: Core Concepts and Techniques

   1. Chapter 1: Introduction to NLP
   2. Chapter 2: Text Representation and Language Modeling
   3. Chapter 3: Text Classification, Sentiment Analysis, and Summarization
   4. Chapter 4: Introduction to Knowledge Graphs
   5. Chapter 5: Applying KGs in NLP

2. Part 2: Vector Databases and LLM Strategies

   1. Chapter 6: Deep Dive into Vector Databases
   2. Chapter 7: Introduction to Large Language Models
   3. Chapter 8: Choosing and Training LLM Architectures
   4. Chapter 9: Data Preparation and Training of LLMs
   5. Chapter 10: Fine-tuning, Adaptation, Evaluation, and Debugging of LLMs

3. Part 3: RAG with LLM

   1. Chapter 11: Understanding Retrieval Augmented Generation (RAG)
   2. Chapter 12: Building Retrieval-Augmented LLM Systems
   3. Chapter 13: Real-World Applications of RAG and LLMs

4. Part 4: Applications, Deployment, and Future of LLMs

   1. Chapter 14: LLMs in Creative Applications
   2. Chapter 15: LLMs in Dialogue Systems and Chatbots
   3. Chapter 16: LLMs for Information Retrieval and Understanding
   4. Chapter 17: Future Directions, Challenges, and Responsible AI
   5. Chapter 18: Evaluation, Deployment, and Future Trends

Notebooks

You can run the provided notebooks in Google Colab. Simply click on the badge links below:

• Chapter 1:

License

This project is licensed under the [License Name] - see the LICENSE.md file for details.