Mastering LLM Applications with LangChain and Hugging Face

The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on. 

This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing.

As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews.

KEY FEATURES  

• Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts.
• Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data.
• Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud.

WHAT YOU WILL LEARN

• Basics of Python, which contains Python concepts, installation, and code editors.
• Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain.
• LLMs and their importance in the cutting edge of AI.
• Creating chatbots using custom data using open source LLMs without spending a single penny.
• Integration of chatbots with real-world applications like Telegram.

WHO THIS BOOK IS FOR

This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment.

1. Introduction to Python and Code Editors
2. Installation of Python, Required Packages, and Code Editors
3. Ways to Run Python Scripts
4. Introduction to NLP and its Concepts
5. Introduction to Large Language Models
6. Introduction of LangChain, Usage and Importance
7. Introduction of Hugging Face, its Usage and Importance
8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub
9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models
10. Integrating LLMs into Real-World Applications–Case Studies
11. Deploying LLMs in Cloud Environments for Scalability
12. Future Directions: Advances in LLMs and Beyond
Appendix A: Useful Tips for Efficient LLM Experimentation
Appendix B: Resources and References

Hunaidkhan Pathan currently serves as a Data Science Lead for a leading consulting firm with over a decade of experience in the field. Specializing in machine learning and artificial intelligence, he brings a wealth of expertise to his role. Hunaidkhan holds a PGDM in Data Science from Shanti Business School in Ahmedabad and a degree in Electronics and Communication Engineering from Gujarat Technological University.

He has significantly contributed to the data science community, with his research papers selected and presented at the prestigious SAS Analytics Conference 2013 in Orlando. The titles of his papers include “Marketing Mix Modeling” as an author and “Predicting market uncertainty with Kalman filter” as a co-author. He was also a LinkedIn Top Voice for Data Science and Artificial Intelligence in 2023. He posts regularly on LinkedIn about Generative AI.

Hunaidkhan is an acknowledged Subject Matter Expert (SME) in Generative AI and Natural Language Processing. His diverse experience spans various LLM services such as OpenAI, Nvidia Nemo, Anthropic, GCP Generative AI, and AWS Bedrock, in addition to numerous open-source LLMs. His broad experience and profound knowledge make him a valuable contributor in the domain of data science.

Nayankumar Gajjar, has a rich background in Data Science, Machine Learning and Generative AI fields with 9 years of extensive experience as a Data Scientist, Machine Learning Engineer, and Python Developer. Over the years, he has made significant contributions to various high-impact projects, showcasing his expertise in statistical modeling, Generative AI, MLOps, and Cloud Computing. This diverse skill set makes him a versatile and highly skilled professional in the Data Science and Machine Learning domains. He holds a master’s degree in Decision Science, further solidifying his deep understanding of the field. In addition to his professional work, he is a YouTuber and a blogger who shares his experiences and knowledge, offering a complete understanding of statistics and providing detailed coding tutorials. His commitment to education extends to his role as a visiting faculty member, where he has taught Python, SQL, Data Science, and NLP courses. He also co-authored a research paper titled “Thiessen Polygon, A GIS approach for Retail Industry in SAS,” which was presented at the prestigious SAS Analytics Conference 2013 in Orlando.